Neutrophils play a central role in eliminating bacterial pathogens, but may also contribute to end-organ damage in sepsis. Interleukin-8 (IL-8), a key modulator of neutrophil function, signals through neutrophil specific surface receptors CXCR-1 and CXCR-2. In this study a mechanistic computational model was used to evaluate and deploy an extracorporeal sepsis treatment which modulates CXCR-1/2 levels. First, a simplified mechanistic computational model of IL-8 mediated activation of CXCR-1/2 receptors was developed, containing 16 ODEs and 43 parameters. Receptor level dynamics and systemic parameters were coupled with multiple neutrophil phenotypes to generate dynamic populations of activated neutrophils which reduce pathogen load, and/or primed neutrophils which cause adverse tissue damage when misdirected. The mathematical model was calibrated using experimental data from baboons administered a two-hour infusion of E coli and followed for a maximum of 28 days. Ensembles of parameters were generated using a Bayesian parallel tempering approach to produce model fits that could recreate experimental outcomes. Stepwise logistic regression identified seven model parameters as key determinants of mortality. Sensitivity analysis showed that parameters controlling the level of killer cell neutrophils affected the overall systemic damage of individuals. To evaluate rescue strategies and provide probabilistic predictions of their impact on mortality, time of onset, duration, and capture efficacy of an extracorporeal device that modulated neutrophil phenotype were explored. Our findings suggest that interventions aiming to modulate phenotypic composition are time sensitive. When introduced between 3–6 hours of infection for a 72 hour duration, the survivor population increased from 31% to 40–80%. Treatment efficacy quickly diminishes if not introduced within 15 hours of infection. Significant harm is possible with treatment durations ranging from 5–24 hours, which may reduce survival to 13%. In severe sepsis, an extracorporeal treatment which modulates CXCR-1/2 levels has therapeutic potential, but also potential for harm. Further development of the computational model will help guide optimal device development and determine which patient populations should be targeted by treatment.
Sepsis occurs when a patient develops a whole body immune response due to infection. In this condition, white blood cells called neutrophils circulate in an active state, seeking and eliminating invading bacteria. However, when neutrophils are activated, healthy tissue is inadvertently targeted, leading to organ damage and potentially death. Even though sepsis kills millions worldwide, there are still no specific treatments approved in the United States. This may be due to the complexity and diversity of the body's immune response, which can be managed well using computational modeling. We have developed a computational model to predict how different levels of neutrophil activation impact survival in an overactive inflammatory conditions. The model was utilized to assess the effectiveness of a simulated experimental sepsis treatment which modulates neutrophil populations and activity. This evaluation determined that treatment timing plays a critical role in therapeutic effectiveness. When utilized properly the treatment drastically improves survival, but there is also risk of causing patient harm when introduced at the wrong time. We intend for this computational model to support and guide further development of sepsis treatments and help translate these preliminary results from bench to bedside.
Funding: This work was supported by National Institutes of Health GM105728-02 (http://www.nih.gov/) (to GC), National Institutes of Health T32 EB009403 (http://www.nih.gov/) (to RS), National Institutes of Health T32 HL076124 (http://www.nih.gov/) & Gerald E. McGinnis Bioengineering Graduate Fellowship (to AM). Animal data collection was sponsored by GlaxoWellcome, Greenford, U.K (http://www.gsk.com/) (to HR). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Sepsis, a systemic inflammatory response due to an infection, affects 900,000 Americans per year and its incidence is expected to increase over the next 10–20 years as the population ages . While it is acknowledged that sepsis is a growing problem, its associated mortality rate has remained persistently high for the last 20 years and is currently near 20% [1–4]. Sepsis is now the leading cause of in-hospital death in the United States, yet there are no FDA approved specific treatments . While understanding of the underlying mechanisms in sepsis has been rapidly improving, translation to clinically effective treatments has proven very challenging [6,7]. Much of this difficulty translating treatments may be the diversity and complexity of individual immune response and patient population [8,9]. These complexities lend themselves well to computational modeling, which can help integrate these complexities into a unified pathophysiological framework and optimize potential treatments .
Neutrophils are one of the first responders to sites of inflammation and play a critical role in the innate immune response. When effective, neutrophils migrate from the bloodstream through endothelial walls to the site of inflammation by sensing gradients of chemokines, which bind to neutrophil cell surface receptors. In early stages of sepsis neutrophils potentially play a duplicitous role, both actively fighting the invading pathogen but also contributing to undesirable systemic inflammation, which often leads to multiple organ dysfunction, immune paralysis, or death [11,12]. Neutrophils' roles in sepsis are well recognized but the dynamics of multiple phenotypes and their impact on treatments is not fully understood. A key chemokine impacting neutrophil behavior and phenotype is interleukin-8 (IL-8). IL-8 signals through functionally distinct surface receptors CXCR-1/2, which are primarily expressed on neutrophils. CXCR-1 is primarily responsible for activating phospholipase D , which mediates respiratory burst and other pathogen killing functions. CXCR-2 has been shown to stimulate migratory functions such as chemotaxis and diapedesis [14,15].
The motivation of this work is to use computational modeling of CXCR-1/2 signaling, and the associated dynamics in neutrophil phenotype composition, to explore whether modifying this dynamic could be exploited to favorably impact outcome in sepsis. A population based mechanistic computational model, which incorporates both receptor level dynamics and neutrophil response to pathogen, was developed to explore the mechanisms involved in sepsis progression and calibrated in septic baboons. Furthermore, an experimental extracorporeal treatment which modulates CXCR-1/2 receptor levels was evaluated in silico using the model framework. The computational model described in this manuscript provides a physiologic rationale for neutrophil's CXCR-1/2 mediated activity in sepsis, delivers insight into the overriding mechanisms involved, and suggests that interventions aiming to modulate phenotypic composition are time sensitive.
Of the 16 baboons subjected to bacterial infusion, 11 (69%) died and 5 (31%) survived, with death occurring within 6 days of bacterial infusion. Based on these two systemic outcomes, a thorough investigation of the model (see Methods section & Fig 1) was completed to identify parameter regimes that explain the dynamics of each group of the responders.
Fig 1. Model diagram detailing neutrophil phenotypes and critical feedback loops.
The system is divided into modules based on the level at which the interactions occur. The systemic level includes the interactions between the pathogen (P), four neutrophil phenotypes (basal: NB, migratory: NM, killing: NK and killing and migratory: NK/M) and chemokine IL-8. The receptor level interactions include the intracellular dynamics of CXCR-1/2, namely activation, internalization and recycling. Two types of feedback occur between the two levels, active surface receptors can trigger the phenotype conversion of the neutrophils and IL-8 produced at the systemic level triggers the trafficking of the receptors. A CXCR-1/2 independent activation via fMLP is included to model general pro-inflammatory response. The systemic damage (D) indicates the overall damage (direct and indirect) caused by the action of the killer neutrophils.
The initial conditions for the state variables of the ODE were fixed to simulate experimental stimulation (Table 1). Among the rate parameters, some were fixed to literature values. These included pathogen growth and decay rates, basal decay rates of naïve neutrophils, CXCR-1/2 internalization and recycling rates and creatinine decay rate (See fixed parameters in Tables 2 and 3). Remaining parameters were estimated by generating parameter ensembles using a Bayesian parallel tempering approach that fit our model to the survivor and non-survivor experimental data sets (see Methods). We conducted the parameter estimation process in two rounds. In round one, the model was fitted to the two data sets separately. By fitting to the two data sets separately, we were able to effectively show that the model was capable of replicating both lethal and non-lethal outcomes through only a change in few parameters. In an attempt to classify the underlying differences, we identified the parameters that were most influential in determining the outcome (survivor or non-survivor) of an individual using stepwise logistic regression. This resulted in a list of seven key parameters. These parameters tend to control the rate at which neutrophils grow and how quickly they can change phenotypes, which play a critical role in determining how quickly and severely the animal will respond to the infection.
Table 2. Shared parameter values.
Table 3. Unique parameter values.
Once these differentiating parameters were identified, we put the model through a second round of estimation. In the second round, the model was fit to both data sets simultaneously; allowing only the seven previously identified key parameters to vary between the survivor and non-survivor subpopulations (see Table 3). Additionally, two fixed parameters were allowed to take different values across the two populations to maintain the appropriate initial conditions in creatinine and white blood cell count. This step resulted in two new parameter ensembles that were identical in 28 parameters but varied in nine parameters. This second step enabled us to better crystallize the differences between animals that survived and those that died. These ensembles are biologically more relevant as we expect the animals' immune responses to be highly similar, with small but important differences indicating susceptibility to a septic insult. Resulting full marginal distributions for each of the 7 parameters were statistically different across survivor and non-survivor populations (Fig 2). The final mean values and the standard deviation of all the estimated parameters are summarized in Tables 2 and 3.
Fig 2. Posterior distributions of parameters allowed to vary across ensembles.
Each parameter was fit separately to data from surviving and non-surviving animals. Values for the mean, 25th-75th percentile, and 2.5th to 97.5th percentiles are shown. Parameters distributions were compared using a two-sample Kolmogorov-Smirnov test. *p<0.05, **p<0.01, ***p<0.001.
The two ensembles resulted in model fits that faithfully recreate the key features of the surviving and non-surviving data sets (Fig 3). Pathogen dynamics showed a transient behavior, with the model predicting a slightly higher peak for non-survivors. The ensembles captured the transient peak in IL-8 that occurs early after infection, with the non-surviving population exhibiting a higher maximum peak. The predicted neutrophil populations also tracked well with the experimental results, with circulating basal neutrophils exhibiting a strong initial decline in abundance as the cells are activated and migrate to the site of infection, followed by a growth phase as the body compensates for the infection, and finally a return to baseline levels. While both surviving and non-surviving populations exhibited this trend, the surviving populations had a noticeably higher peak in basal neutrophils during the growth phase. Levels of neutrophil elastase / α1-PI complex in the blood, indicative of the killing and damage causing function of activated neutrophils, peaks around 15 hours post-infection. The non-surviving population showed a stronger and longer lasting peak, which is captured by the model. Creatinine, a measure of kidney health, increased to higher and more sustained levels in non-surviving animals, as kidney health decreases and creatinine was not as efficiently cleared.
Fig 3. Simulated model fits with their experimental training data.
Mean (red), 25th-75th percentile (dark blue), and 5th-95th percentile trajectories of the simulated ensemble are shown. Experimental data points are shown in black with error bars representing one standard deviation above and below the mean. Results are shown for surviving (left) and non-surviving (right) animals for all observables with corresponding experimental data; (A) pathogen levels, (B) free IL-8 levels, (C) white blood cell counts, (D) neutrophil elastase / α1-PI complex levels, and (E) creatinine levels.
The model also made predictions in the absence of observable data on the dynamics of neutrophil phenotypes (Fig 4 & Fig 5). Although both populations had similar peaks in fully activated neutrophils, allowing them both to fight off the infection on similar time scales as predicted experimentally, they showed strong differences in other populations. Non-survivors showed a significantly stronger spike in damage-causing killer neutrophils, while survivors showed a stronger spike in migratory neutrophils. This can also be seen in the parameter ensembles, as neutrophils in non-survivors had an increased proclivity to activate their killing function in response to IL-8, while neutrophils in survivors were faster to activate their migratory functions (Fig 2). Generating similar numbers of fully activated neutrophils, but through differing intermediate activation populations, could be an explanation for how these two animal populations controlled infection with similar dynamics, while still experiencing differing fates.
Fig 4. Model predictions for neutrophil phenotype dynamics following infection.
Mean (red), 25th-75th percentile (dark blue), and 5th-95th percentile trajectories of the simulated ensemble are shown. Predictions are shown for surviving (left) and non-surviving (right) animals for the four neutrophil phenotypes considered in the model; (A) basal neutrophils, which were calibrated with white blood cell count data, as well as (B) migratory neutrophils, (C) killer neutrophils, and (D) killer/migratory neutrophils for which there is no experimental data.
Fig 5. Model predictions for maximal levels of each neutrophil phenotype compared across ensembles.
Maximal values for each neutrophil phenotype from each trajectory in both ensembles were recorded. Values for the mean, 25th-75th percentile, and 2.5th to 97.5th percentiles are shown. Distributions were compared using a two sample T-test. *p<0.05, **p<0.01, ***p<0.001.
At the receptor level, underlying activation of CXCR-1/2 was transient in both the survivors and non-survivors (S1 Fig). Compared to the neutrophil dynamics which was slow and spread across few hours, receptor dynamics was very fast. Most of the receptors were in the free state, and internalized CXCR-1 is recycled faster than CXCR-2. Among the active receptors, there was one order of magnitude higher level of internalized CXCR-1 receptors than the surface bound CXCR-1 receptors, while this difference is two orders of magnitude for CXCR-2. Non-survivors had higher levels of the surface and internalized active receptors. This can be explained by the higher peak in IL-8 levels for the non-survivors than the survivors (Fig 3). But, survivors had very close levels of CXCR-1 and -2 bound receptors and non-survivors had slightly higher levels of bound CXCR-1 than bound CXCR-2. These small differences in the peak levels of the receptors coupled with differences in the transition rates were sufficient to result in different neutrophil phenotype levels in the two populations, a key prediction from the ensemble modeling process.
Until now, the focus was on deriving parametric ensembles explaining the mechanism of sepsis progression in each population. In this section, the sensitivity of sepsis-mediated damage to different model parameters (and hence different processes in the network) was evaluated for each population. Area under the damage curve (AUCD) was used as an output metric of cumulative damage from sepsis. The analysis was done in two steps. First the sensitive parameters affecting damage in each population was identified to check if similar parameters were responsible for modulating damage within each population. Next, the two populations were combined to identify the parameters primarily responsible for a switch from a low to a high damage region. Since the model is highly nonlinear, a global sensitivity analysis (GSA) based on variance decomposition was chosen. This method decomposes the total variance in the output into variance and co-variance contributions from each rate parameter and its higher order combinations. To reduce computational cost, a meta-model based approximation was done (See Materials and Methods). The meta-model method called Random Sampling High Dimensional Model Representation (or RS-HDMR), decomposes the output function (AUCD) into a set of component functions that includes the mean followed by first order effects of each parameter and other higher order effects resulting from parameter combinations. The degree of sensitivity of a parameter or its combination with other parameters (as a set) is captured by Sobol' index which by definition is the fraction of the total output variance attributed to the selected parameter set. To perform GSA, 4000 samples were generated from the parameter distributions of the two ensembles and the dynamics of the damage term was simulated for the survivors and the non-survivors. Fig 6(A) shows the AUCD distributions for each ensemble. As expected, the survivors show lower levels of cumulative damage than the non-survivors. The coefficient of variation was higher for the non-survivors (CV = 1.98) as compared to the survivors (CV = 0.32). When GSA was performed on the survivor and non-survivor samples separately and in combination, it was found that a third order RS-HDMR contributed close to 95% of the variance for both the populations. However, most of the important contributions were from the parameters constituting highly ranked first order indices. Fig 6B and 6C shows the first order and total Sobol' indices for the first five most sensitive parameters of each population and Fig 6(E) shows the results when both populations are combined. Note that the total Sobol' index for each parameter, is the sum of first order index and all higher order indices involving that parameter.
Fig 6. Factors affecting cumulative systemic damage.
(A) Cumulative damage seen in survivors and non-survivors. The histograms show the area under the damage curve until 144 hr. The rate parameters were sampled from the generated ensemble for each population. The distribution used for GSA contains 4000 samples for each population. (B-C) Prime drivers of cumulative damage. First order and total effect Sobol' indices which explained most of the variance are tabulated here for the survivor and non-survivor population respectively. (D) Functional dependence of AUCD on killer cell decay rate for the survivors (S) and non-survivors (NS). The green line has been added for visual guidance of the trend and is based on the mean trend identified by the RS-HDMR component functions. For each population, damage decreases with increase in the decay rate of the killer neutrophil. (E) Prime drivers of cumulative damage for the combined population. (F) Functional dependence of AUCD on CXCR1 induced naïve to killer neutrophil transition rate for the survivors and non-survivors. The green line shows that within the population, damage is not particularly sensitive to the transition rate, but increased transition rate could be responsible for higher damage levels seen in non-surviving population.
For GSA conducted separately on the survivor and non-survivor ensembles, it is found that damage is mainly determined by the decay rate of the killer neutrophils, (direction of influence shown in Fig (6D)). The decay rate of the killer neutrophil controls the rate at which killer neutrophils are removed from the system, and the faster these neutrophils are removed, the lesser the damage. The next important term is the direct damaging effect of the killer neutrophils and this parameter has significant second order interactions with other parameters of the model as seen from the total sensitivity index. The next set of parameters has secondary importance and these parameters are different for the two populations (variance contributions of each parameter in this set is in the range, 1–10%). In survivors, damage is more influenced by the production rate of basal neutrophils and IL-8 in presence of the pathogen. In non-survivors, the effect is more pronounced for damage mediated IL-8 production (a positive feedback component), damage recovery term and killer neutrophil production rate. This indicates that overall damage in non-survivors is more sensitive to the parameters associated with killer cells, IL-8 and damage.
For GSA conducted on the combined population, the decay rate of killer neutrophils remains the most important parameter. Interestingly, the sensitivity value and ranking of three parameters increase relative to the case where the populations are analyzed separately. Among these, the transition rate of naïve neutrophils to the killer phenotype via CXCR1 ( ) is the most important parameter. The next two parameters include the decay rate in filter Eq (7) (which determines the delay between pathogen generation and resulting neutrophil entry into circulation during sepsis) followed by the parameter controlling transition rate of killer neutrophil to the dual phenotype by CXCR2. Functional dependence of damage on these three parameters shows that they could be responsible for shift in the population from a low to a high damage region. For example, Fig 6(F) shows the dependence of AUCD on parameter . Within each population, no particular trend is visible, but relative increase in the transition rate in the non-survivors correlates well with increased damage. Results in Fig 2 showed that the ranges of two of the parameters, and kfilter_off were significantly different for the survivors and non-survivors. Results from sensitivity analysis support this prediction and further show that the parameter values correlate well with the transition in observed damage.
Extracorporeal devices are emerging as promising therapies for treatment of sepsis[16–19]. In this instance we propose extracorporeal treatment which directly modulates CXCR-1/2 levels using a bioactive surface which interacts with unbound neutrophil surface receptors upon contact. Such a device, which is currently under development at the University of Pittsburgh, generates targeted and controlled downregulation of neutrophil surface receptors. The dynamics of this device can be analyzed within the framework of the generated computational model to determine its proof of principle in silico and help optimize treatment parameters. The proposed treatment implementation is shown in Fig 7. Specifically, the receptors are allowed to go to a trapped state and become unavailable for activation by IL-8 for the indicated time of treatment. To evaluate the potential of such an immunomodulatory treatment, we next performed an in silico trial by varying (1) the time when the treatment is introduced and removed and (2) the strength of interaction between the trapping device and the unbound neutrophil surface receptors.
Fig 7. Model diagram showing receptor level treatment implementation.
The extracorporeal treatment introduces a trapped receptor state for CXCR-1/2. This state prevents IL-8 induced phenotype transition, which limits NK generation. The treatment is modeled entirely in the receptor level of model, leaving the systemic level (see Fig 1) unchanged.
For the analysis, the treatment initiation time was varied between 0 and 12 hours after the initial infection and the treatment discontinuation time was varied between 0 and 100 hours after infection. To modulate the treatment intensity, the device-receptor Kd was varied between the 1x10-2 M and 1x10-5 M, with 2.5e-3 M representing the Kd of IL-8 and the receptors. The treatment was tested on a simulated population constructed by randomly selecting 69% of parameter sets from the non-survivor ensemble and 31% of parameter sets from the survivor ensemble, as observed in the experimental population. Survivor rate was measured for each set of proposed treatment parameters, as determined by the logistic regression classifier trained on the parameter ensembles with no treatment. A survivor rate above 31% was considered an improvement over baseline, and below 31% indicated the treatment causing overall harm.
Fig 8 shows the survival rate following different treatment strengths and start-end times. In general, the optimal time for beginning treatment was between 3 and 6 hours after the original infection, resulting 40–80% survival rates depending on treatment strength. Starting the treatment after six hours was typically too late to have a strong effect on survival. Starting treatment within 3 hours of infection would often have neutral or deleterious effects, as it would dampen the initial inflammatory response that is critical to fighting off the infection. This led to an increase in pathogen growth and an increased late inflammatory response once treatment was removed. In the worst case scenarios following early treatment of a short duration, survival rates dipped as low as 13.2%, and this trend could be seen across all treatment strengths.
Fig 8. Effects of simulated treatment on animal survival rates.
Survival rates of a simulated population of animals following treatment with the proposed extracorporeal device considering a device-receptor affinity of (A) 1x10-2 M, (B) 1x10-3 M, (C) 1x10-4 M, (D) 1x10-5 M. In all cases the time of treatment was varied between 0 and 12 hours post infection and ended between 0 and 100 hours post infection.
When treated at the optimal time, survival rates increased from the 31% baseline to greater than 80% with sufficient device-receptor affinity. Using a Kd of 1e-2 M results in a maximum survival rate of 47%, and decreasing the Kd to 1e-3 M further increases this rate to 80.3%. Further decreases in the Kd to 1e-4 M and 1e-5 M results in increases in survival rate to 83.1% and 84.4%, showing there is a diminishing return to continuously increasing the device affinity. As the affinity increases, we see a new trend emerge in the simulation results, where treatment that begins as early as the onset of infection and is significantly long lasting leads to increased survival rates, and a less strictly defined optimal treatment time (Fig 8(D)). In this case, the treatment is so strong and long-lasting that the inflammatory response is very strongly suppressed, implying that overwhelming pathogen growth leading to death cannot be reached within the bounds of this. However, this suppression of the immune system allows for significant pathogen growth and could leave the subject vulnerable to secondary infections which are not considered in this model.
Trends in response to treatment also appear to be robust to individual parameter values. The two most sensitive parameters and were varied, increasing and decreasing each by 10% and 50% and recalculated the simulated population response to treatment (S2 Fig and S3 Fig). In general response trends remained the same, with a defined peak in survivorship when treatment is administered 2–4 hours after infection. The magnitude of responses varied predictably, as strongly increasing , the death rate of damage-causing neutrophils, resulted in a higher peak of survival. Conversely, increasing , which corresponds to a faster induction of damaging-causing cells, leads to a slight decrease in survivorship. Varying had a larger effect on these results, as expected following its identification as the model's most sensitive parameter affecting damage (Fig 6).
This manuscript discusses the development of a mechanistic computational model of IL-8 mediated activation of CXCR-1/2 receptors in baboons which were administered intravenous E. coli. Neutrophil phenotypes, which dictate neutrophil functional response, were generated in silico based on CXCR-1/2 surface receptor levels, linking receptor level dynamics with neutrophil functional response. Parameter ensembles were generated for survivor and non-survivor populations, allowing for in silico observation of sepsis progression. Additionally, an extracorporeal treatment which modulates CXCR-1/2 levels on neutrophils was introduced in silico. This proof of concept evaluation allowed for preliminary device evaluation and optimization of treatment parameters.
To our knowledge, this is the first model describing dynamic interactions of neutrophils which specifically takes into account information sharing between the systemic variables and the receptor levels. The receptor level dynamics of the model function on a rapid time scale, adjusting to systemic IL-8 levels in a matter of minutes. These changes in receptor signaling dictate changes in neutrophil phenotype, which dictates neutrophil function and hence mortality. This link thus provides a valuable mechanistic framework that can be subjected to clinically relevant treatment scenarios. For example, the experimental treatment could be implemented purely on the receptor level. Alternatively, systemic variables such as IL-8 levels or neutrophil phenotype could be modulated to evaluate performance of hemoadsorption or neutrophil sequestration extracorporeal devices.
Application of parallel tempering approach for parameter estimation allowed for the efficient generation of ensembles of parameters and resulted in a model that could fit experimental data well , allowing reasonably accurate simulations of the system without making strong claims about the values of single parameters which are notoriously difficult to measure and are likely to vary between individuals. This allows for robust, population-level predictions rather than point predictions of model parameters and model behavior. However, the computed multi-dimensional posterior distribution in parameter space reflects constraints imposed by empirical data, as well as data sparsity and uncertainty. These constraints impose a covariance structure in the posterior distribution such that there is robustness in model behavior, despite large uncertainties in individual parameter values. Learning this structure is likely crucial in building predictive model [21,22]. Yet, the method is making no claim that individual parameter sets in the ensemble represent individuals in a population. At best, an individual could be represented by a smaller ensemble, reflecting uncertainty relating to this particular individual. Yet, it is fair to say that the ensemble is meant to represent uncertainly about a population of individuals, so that simulating the ensemble will provide expected behaviors across a population of individuals, as long as such behaviors are compatible with the empirical data used to generate the ensemble.
One trend that arose in the estimated parameter ensembles was a large difference in the magnitudes of different rate constants, sometimes spanning many orders of magnitude. This is not surprising, due to the inclusion of biological events spanning many time scales, ranging from fast molecular events to cell phenotype transitions and finally to the full duration of infections lasting for days. This suggests that future iterations of the model would benefit from a multiscale approach optimized towards handling these different time scales. Previous efforts [23–25] have worked out approaches that allow for efficient deterministic simulation of fast-scale molecular events, combined with more accurate stochastic simulation of slow-scale or rare events, and such techniques have resulted in impressive results [26,27].
Sensitivity analysis on the parametric ensembles enabled identification of the relative importance of the model parameters to state variables of the model. In general, sensitivity analysis is an important step in systems biology workflows and provides valuable information on model characteristics [28,29]. Most models in the literature resort to a local analysis which is sufficient if the parameters are well defined. For nonlinear dynamic models based on sparse experimental data and for systems which have inherently high parametric uncertainty, a global analysis needs to be done. Global techniques perform combinatorial perturbations of the parameters utilizing samples from the high-dimensional space. Application of meta-modeling approximations via RS-HDMR as was done in this work can significantly reduce the computational cost of sampling requirements for global methods. Additionally, if the sampling process takes into account parameter covariance computed from an ensemble model, biologically relevant sensitivity indices can be obtained. The systematic integration of ensemble modeling and global sensitivity analysis in this work allowed for identification of the parameters that control biological outcomes like sepsis induced tissue damage.
In addition to parameter fits, the behavior of the non-fitted state variables were inspected to check for features relevant to a clinical prognosis. Sepsis progression was analyzed by comparing differences between survivor and non-survivor populations. Neutrophil phenotypes in particular give insight into the differences between survivors and non-survivors. Of importance is the killer neutrophil population, which is highly elevated in the non-survivor population (see Figs 4 & 5). This neutrophil phenotype is associated with neutrophil induced tissue damage in the model. With support from sensitivity analysis, killer neutrophil decay rate, which sets the levels and dynamics of NK, was found to be the most important contributor to total damage in both the populations. Multiple studies support this finding, indicating that non-survivors or those with more severe sepsis experience increased levels of neutrophil induced tissue damage and MPO generation [11,30–33]. Furthermore, the importance of this term is supported by studies on neutrophil apoptosis and lifespan. Research by Taneja  and Fialkow  determined that neutrophil apoptosis was reduced in cases of severe sepsis, leading to increased lifespan of primed and activated neutrophils. Damage caused by these neutrophils was partially responsible for the progression of sepsis in these severe cases. Upon completion of the combined GSA, was also found to be a significant contributor to total damage. Increase of this term leads to preferential generation of the NK neutrophil phenotype, which directly contributes to tissue damage.
On the other hand neutrophils in the migratory phenotype were similar in survivor and non-survivor populations. These findings agree with the data from Cummings et al  which found neutrophil's harvested from septic and non-septic patients migrated to IL-8 at similar levels. Interestingly, survivors and non-survivors had similar levels of neutrophil kill/migrate phenotype, indicating that both ensembles had adequate neutrophil populations to eliminate the source pathogen. Therefore, the additional damage in non-survivors was neutrophil induced resulting from elevated neutrophil killer phenotype levels. The IL-8 mediated killing functions of neutrophils are primarily triggered through CXCR-1 rather than CXCR-2. Modulation of CXCR-1 levels in particular may reduce the killing neutrophil phenotype and reduce neutrophil induced organ damage.
A number of experimental treatments for sepsis and other acute inflammatory diseases have targeted the CXCR-1 receptor with success in animal models [36–38]. However, translation to humans has been difficult for two main reasons . First are inherent species dependent differences between human and animal immune systems that must be recognized and accounted for in pre-clinical studies. Second is the misuse of animal models and misinterpretation of pre-clinical data . The recent debate on the translational fidelity of critical disease mouse models is a prime example where two separate comparisons of the human versus mouse genomic leukocyte responses using the same database resulted in two contradictory conclusions [40,41]. In the case of IL-8 signaling, which is not present in murine models, homologous cytokines and their associated surface receptors must be examined in IL-8's place . In this context, in silico modeling is an attractive alternative given that it allows preliminary evaluation of experimental human treatments at minimal costs.
Multiple extracorporeal sepsis treatments are currently under investigation with promising results. Blood purification techniques such as hemoadsorption [16,17,43–45] allow for cytokines and other detrimental proteins to be removed directly from the blood during the cytokine storm, curbing the patient's immune response. Another approach called activated neutrophil sequestration [19,46], selectively removes harmful neutrophil phenotypes from circulation. In this instance we propose extracorporeal treatment which directly modulates CXCR-1/2 levels using a bioactive surface which interacts with unbound neutrophil surface receptors upon contact, resulting in CXCR-1/2 downregulation. This approach is advantageous because no components of blood are removed from circulation, allowing for a healthy immune response after appropriate modulation of neutrophil surface receptors. In addition, all necessary cell-cell interactions are allowed to occur within well-controlled microcirculation of the device. Such a setup also allows treatment to be easily titrated or halted by adjusting blood flow through the device. The dynamics of such a device were analyzed within the framework of the generated ensemble model to determine its proof of principle in silico and to evaluate its benefits in rescuing individuals marked as non-survivors by the parameter ensembles.
When evaluated in silico the proposed extracorporeal CXCR-1/2 modulation device improved mortality from 31% to above 80% when deployed under certain ranges of conditions. This substantial improvement in survival supports the hypothesis that a CXCR-1/2 modulatory device may improve patient outcomes. However, time and length of treatment implementation are critical parameters tied to this success. The importance of quickly beginning sepsis treatment has been well established , particularly for antibiotic administration. Our simulations showed a well-defined optimal time for the initiation of treatment, between 3 and 6 hours after the onset of severe infection. Treatment, if started within this time frame, had a high degree of success over a large range of treatment durations and strengths. This window is specific to the animal model under study and will not directly translate to a clinical setting for two main reasons. First, the model was calibrated with experimental data obtained from baboons, and differences between the baboon and human immune systems must be considered. Second, the baboons were exposed to a well-controlled bacterial infusion at a known time point, followed by a predictably quick and strong immune response. In this instance the pathogen load is well controlled and a large portion of the ensemble can therefore be addressed by a single treatment setting. In clinical practice, patients present with varied pathogen loads and they may be in different stages of infection and immune response. So, future experiments will need to combine clinical knowledge with additional data gathering and simulation to obtain treatment timing relevant for human patients.
Clinicians are actively searching for biomarkers to track sepsis disease progression and prescribe treatment [48–50]. Neutrophil phenotype may be a valuable indicator of disease state and individual patient response, but this information is difficult to collect in the clinic. Currently neutrophil phenotype can be evaluated either through functional testing or flow cytometry analysis of critical neutrophil surface receptors. In addition to CXCR-1/2 which are the focus of this model, CD11b, CD88, and CD62L all have roles in dictating neutrophil phenotype  and surface receptor expressions vary depending on severity of the inflammatory response. To more readily exploit phenotype data it may be possible to map neutrophil function to easily measurable biomarkers. Using these indirect measures of neutrophil phenotype can guide clinicians to ideal treatment regimens.
In conclusion, the ensemble model presented in this report provided key insights into the progression and mechanisms involved in progression of sepsis. We underline the role of relative abundance of killer, migratory and dual neutrophil phenotypes in deciding survivorship in an animal model. In addition, an in silico extracorporeal treatment which modulates CXCR-1/2 neutrophil surface receptors showed promising results. Further study and collection of experimental data will help further refine both the model and experimental device. Incorporation of data from a diverse patient population and expansion of current ensembles would increase the model's generalizability, improving the potential for translation. Additional model parameters related to the device such as flow rate, surface area, and form factor could be included, allowing the model to streamline device development.
After general anesthesia, instrumentation and a 30 minute stabilization period, sixteen baboons (Papio ursinus) weighing between 19 and 32 kg were infused with 2 x 109 CFU Escherichia coli per kg over a two-hour period as described previously . Thereafter, antibiotic therapy was delivered (gentamycin 4mg/kg twice a day). Eight animals were placed in an acute study lasting 6 days, while another eight were placed in the chronic study intended to last 28 days. All animals were observed for a 4-hour period after bacteria infusion then 11, 23, 35, 47, 72 hour and 6 days after infusion. Pathogen counts in blood, IL-8, creatinine, white blood cell, neutrophil elastase / α1-PI complex, and other physiologic parameters and biomarkers were gathered at multiple time point. For animals in the chronic study an additional time point was collected at 28 days. At the end of the study period, the baboons were again anesthetized for measurements and thereafter sacrificed with an overdose of pentobarbital. This study was approved by the Institutional Animal Care and Use Committee at Biocon Research Institute and animals were treated according to NIH guidelines.
A simplified mechanistic model of IL-8 mediated activation of CXCR-1/2 receptors and neutrophil response to a pathogen was developed based on available literature information and general knowledge of acute inflammatory response. Receptor level dynamics and systemic parameters were coupled with multiple neutrophil phenotypes to generate dynamic populations of activated neutrophils which reduce pathogen load, and/or primed neutrophils which cause adverse tissue damage when misdirected. Mathematical representation of the interactions detailed in Fig 1 were generated using ordinary differential equation (ODE) framework with the rate of interactions described by mass action kinetics or Hill type kinetics [53,54]. The interactions included in the model gives rise to 16 ODE state variables and 43 rate parameters.
In brief, the model is initiated by a pathogen load, which represents a bacterial inoculation. Presence of pathogen leads to continued growth as well as IL-8 and fMLP cytokine production. IL-8 is generated indirectly from pathogen generation from responding phagocytic mononuclear cells . IL-8 initiates CXCR-1/2 activation in the receptor level, which in turn generates neutrophil phenotype change. Depending on phenotype, neutrophils may cause either pathogen elimination or misdirected tissue damage. A systemic damage indicator represents overall patient health. Increased systemic damage results in further IL-8 generation [56,57], resulting in a positive feedback loop. This simplified system captures the basic functionality of acute IL-8 mediated immune response to pathogen and is capable providing valuable feedback on potential therapeutic treatments modulating these mechanisms. A more detailed description of model equations follows.
Eq (1) describes the population of foreign pathogen. Base pathogen growth rate increases linearly with pathogen until approaching a carrying capacity at elevated pathogen loads. In addition to basal pathogen death, the Neutrophil kill/migrate phenotype is capable of decreasing pathogen population through diapedesis, followed by targeted phagocytosis [11,58,59].
Ligands: Interleukin-8 (IL-8) and fMLP.
In the model, neutrophils progress through multiple phenotypes which dictate neutrophil migratory, phagocytic, and antibiotic activity. The association of chemokine IL-8 with the surface CXCR-1/2 triggers the transition of basal neutrophils to functional phenotypes. Previously characterized receptor surface activation, internalization, and recycling rates of CXCR-1/2 are utilized to predict receptor levels and neutrophil phenotypes in response to systemic IL-8 stimulation [14,60]. IL-8 production rate is a function of elevated pathogen and tissue damage [61,62]. Both terms are represented as Hill Equations in Eq (2). While IL-8 is not directly linked to pathogen levels, this simplified representation captures IL-8 release from macrophages and endothelial cells in response to infection.
Eq (3) characterizes a general pro-inflammatory pathway, which is independent of CXCR-1/2 activation has been added to represent alternate means of neutrophil induced pathogen activation. This generic pathway is not modeled using receptor level dynamics and directly transitions the NBasal (NB) population to NKilling/Migratory (NK/M).The generic proinflammatory ligand growth is dictated by pathogen level.
Neutrophil Surface Receptors CXCR-1 & CXCR-2.
Receptor level dynamics dictate neutrophils advancement into one of four phenotypes depending on CXCR-1/2 surface activation. Each receptor can occupy one of the three states, namely free surface receptor, surface receptor bound to IL-8 and internalized receptor bound to IL-8 . Eq (4) and Eq (5) describe CXCR-1 surface and internalized populations, which have been non-dimensionalized to remove the free receptor state. Equivalent equations are present for CXCR-2. The active surface state was modeled as the dynamic condition which drives neutrophil population phenotype change . This model makes the assumption that CXCR-1/2 receptors are conserved.
Eq (6) represents the resting state (NB) represents basal neutrophils which have not been stimulated by IL-8 or other proinflammatory stimuli. These neutrophils are mobile in blood, but not capable of causing systemic damage or utilizing their anti-pathogen capacity without transitioning to another phenotype. All neutrophils begin in this basal state prior to activation and priming. Without stimulation, neutrophil growth and death rates are in equilibrium, however growth rate increases with the introduction of pathogen, which has been expressed through a filter equation to produce a physiologic time delay [11,65]. CXCR-1/2 surface complex levels dictate the transition rates of NB to the NMigratory (NM) or Nkilling (NK) phenotypes. Additionally, there is a direct pathway to transition NB to NK/M. This mechanism represents a general proinflammatory process independent of CXCR-1/2 signaling. A filter equation was generated in Eq (7). This function fits the physiologic delay between pathogen generation and increased neutrophils entering circulation.
Eq (8) contains neutrophils which have been activated via IL-8 mediated CXCR-2 stimulation.
Eq (9) characterizes the killing phenotype (NK), representing neutrophils which have been activated via IL-8 mediated CXCR-1 stimulation. NK neutrophils are capable of untargeted cytotoxic activity, resulting in systemic organ damage. The CXCR-1/2 surface population dictates transition rates into phenotypes. Neutrophil elastase / α1-PI complex was utilized in the model to fit NK neutrophil population. As shown in Eq (10) levels of neutrophil elastase / α1-PI complex equate to levels of circulating NK phenotypes.
Both NM and NK phenotypes are capable of progressing to the NK/M phenotype through CXCR-1/2 surface receptor activation. This neutrophil state (NK/M), shown in Eq (11), represents neutrophils which have been activated through both CXCR-1 and CXCR-2 and are capable of target pathogen removal, effectively fighting infection. The pathogen equation (Eq (1)) contains a term which dictates pathogen death in response to NK/M levels. Once activated through CXCR-1/2 neutrophils are not capable of returning to the basal NB phenotype.
A systemic damage indicator (Eq (12)) was developed to represent overall animal health. Damage is increased by the population of NK and decays gradually as tissue and organs recover. Creatinine, a biomarker for kidney function, was utilized in Eq (13) as an indicator for the damage term ensemble computation. Creatinine is maintained at a constant level in the absence of damage, but systemic levels increase with damage as body's ability to clear creatinine decreases .
The model uses empirical time series of Pathogen (CFU), IL-8 (nM), creatinine (mM), White Blood Cell count (103 cells/μl), and neutrophil elastase / α1-PI complex (ng/ml) for computation of the ensemble. State variables and their initial conditions are listed in Table 1.
The model contains 38 parameters, 13 of which are fixed based on literature data (Table 1). Parameter values were inferred using a Bayesian parallel tempering approach [22,67], which utilizes traditional Markov Chain Monte Carlo (MCMC) methods to sample the Bayesian posterior distribution P(p|y), the probability of parameter set p given data y, given by the Bayes formula where L(y|p) is the likelihood of observing y for a model with parameters p, θ(p) is the prior distribution, and ∫L(Y | p)θ(p) is the normalizing constant. Additional sampling efficiency is gained by running multiple parallel chains evolving at different temperatures. Higher temperature increases the likelihood of acceptance of proposed steps. This allows the high temperature chains to move more freely through the parameter space, avoiding getting stuck in local minima. This results in more efficient exploration of parameter space [20,68] a method we have applied extensively in parameter estimation of practically unidentifiable complex non-linear models [10,69,70]. This resulted in the creation of parameter ensembles, where each parameter is represented by a posterior distribution, rather than a single value. Free parameters were fit separately to the survivor and non-survivor experimental data sets, resulting in two parameter ensembles representing surviving and non-surviving animals.
Prior distributions were selected for each parameter. In each case uniform priors were used, with a suitably large range so as to encompass all reasonable parameter values. This was ideal due to the limited prior knowledge and phenomenological nature of many of the parameters. Tighter ranges were enforced on select parameters as required to avoid non-physiologic model behavior. All candidate parameter values were selected from these pre-defined priors.
Where wi,j,k is a weighting function, yi,j,k is the output for a simulation with a single set of parameters, is the experimental mean, and σi,j,k σi,j,k is the experimental standard deviation at time point i, observable j, and data set k. No additional penalties or constraints were added to parameter selection. To ensure proper fitting of the pathogen observable a threshold was added to change all values below the experimental limit of detection (4.4 CFU) to 0.
To efficiently sample the posterior distribution, six separate Markov chains were run, initiated with parameter values randomly selected from the supplied prior distributions which met a maximum energy criterion. Each chain was initiated with a temperature and step size parameter which controlled the chain's ability to fully explore the parameters space. Chains were allowed to swap from a higher temperature to a lower temperature every 25 steps to allow for local sampling of newly found local minima. Step size and temperature parameters dynamically changed every 6,250 and 2,500 steps respectively to attempt to reach an ideal step acceptance rate of 23% , and swap rates of 15%-30%. Once these targets were reached, the temperature schedule and step sizes were fixed. Parameter sets were saved every 25 steps. Full exploration of parameter space was confirmed by examining, for each parameter, the frequency histogram of its full marginal posterior distribution, confirming that it spanned the prior domain.
We measured convergence and chain stationarity using the Gelman-Rubin criteria [72,73]. All parameters had converged with a potential scale reduction factor (PSRF) < 1.1 following 200,000 (x25) MCMC steps. Another 100,000 steps were taken to build a posterior distribution for each parameter that would be used for all model analysis and simulation. This ensured that all samples from the burn-in time for each chain were discarded, and only samples from the correct stationary distribution were used. The ensemble of all parameter sets from the lowest chain comprised the computed ensemble (posterior distribution).
In order to better capture the underlying biological differences between animals that survive and those that die following the same challenge we attempted to identify the most important parameters in determining animal fate. After computing ensembles for survivors and non-survivors, we performed regularized logistic regression, forward conditional stepwise logistic regression, and backward conditional logistic regression to identify a subset of parameters that are most indicative of outcome. Predictors consisted of all estimated parameters of both ensembles, and the indicator variable was the source (survivor or non-survivor) of the ensemble. Parameters were selected that were considered significant by all three methods, leaving a set of seven key parameters.
A second round of model fitting was then performed. In this round, 18 of the 25 parameters were fit simultaneously to both data sets, resulting in identical parameter values in the two ensembles. The seven parameters identified as being significant were fit twice, once against the survivor data set and once against the non-survivor data set, resulting in different parameter values across the two ensembles. This resulted in a smaller and more focused difference between the final ensembles.
For most systems, very high order interactions are negligible and therefore, indices until the third order are sufficient, with most systems requiring only until the second order terms . In this work, we constructed a third order RS-HDMR. All GSA computations were performed using the ExploreHD software (Aerodyne Research Inc., MA, USA).
After model fitting and analysis, a potential extracorporeal treatment was introduced (See Fig 7). The extracorporeal treatment directly modulates CXCR-1/2 levels of circulating neutrophils, limiting passage of NB to NK and NM. This mechanism of limiting CXCR-1/2 surface levels is modeled solely in the receptor level equations of the model. A heaviside function is used to turn treatment on and off at various treatment times. The kft1 parameter represents treatment effectiveness, which combines device size, efficacy, efficiency and flow rate. Eq (14) is the modified CXCR-1 surface receptor equation which includes the Heaviside function. Eq (15) characterizes the trapped receptor state of CXCR-1. Similarly Eq (16) and Eq (17) are constructed for CXCR-2 and its associated trapped receptor state.
In order to implement and evaluate treatment frameworks, simulated patient survivorship needed to be explicitly labeled. This was accomplished using a logistic regression classifier as specified by the machine learning software Weka . The estimated parameter ensemble was partitioned into a training set and test set to build the classifier, using 20% of the ensemble as training data. Two features were used for training, total accumulated damage measured by area under the curve of the damage time course for each patient, as well as the peak damage experienced by the patient. Training with these features resulted in a classifier that could label a patient as surviving or dying after being exposed to a specific infection and possible treatment.
S1 Fig. Model predictions of receptor dynamics following infection.
Mean (red), 25th-75th percentile (dark blue), and 5th-95th percentile trajectories of the simulated ensemble are shown. Predictions are shown for the CXCR1 (A-B) and CXCR2 (C-D) bound to IL-8 and actively signaling from the cell surface, as well as internalized and unable to signal.
S2 Fig. Effects of varying Nk decay rates on simulated treatment.
Survival rates of a simulated population of animals following treatment with the proposed extracorporeal device considering a device-receptor affinity of 1x10-3 M for k_Nk values of (A) 50% above, (B) 10% above, (D) 10% below, and (E) 50% below the baseline vale (C). In all cases the time of treatment was varied between 0 and 10 hours post infection and ended between 0 and 100 hours post infection.
S3 Fig. Effects of varying Nk induction rates on simulated treatment.
Survival rates of a simulated population of animals following treatment with the proposed extracorporeal device considering a device-receptor affinity of 1x10-3 M for k_Nk_IL8 values of (A) 50% above, (B) 10% above, (D) 10% below, and (E) 50% below the baseline estimated value (C). In all cases the time of treatment was varied between 0 and 10 hours post infection and ended between 0 and 100 hours post infection.
Sixteen baboons (Papio ursinus) weighing between 19 and 32 kg were infused with 2 x 109 CFU Escherichia coli per kg over a two-hour period and followed until predetermined time points or death.
The authors acknowledge Dr. Ipsita Banerjee and Dr. James Faeder at the University of Pittsburgh for their valuable guidance in the development of the computational methods and Dr. Justin Hogg for providing the codes used for parameter estimation. The authors would also like to thank Anna Khadem, Eva Tögel, and Mohammad Jafarmadar for technical support and Dr. Marcin Osuchowski for critical review and analysis.
Conceived and designed the experiments: ADM RPS SM WJF GC HR. Performed the experiments: ADM RPS SM HR. Analyzed the data: ADM RPS SM. Contributed reagents/materials/analysis tools: HR GC. Wrote the paper: ADM RPS SM.
22. Brown K, Sethna J (2003) Statistical mechanical approaches to models with many poorly known parameters. Phys Rev E 68 (2): 021904.
23. Haseltine EL, Rawlings JB (2002) Approximate simulation of coupled fast and slow reactions for stochastic chemical kinetics. J Chem Phys 117 (15): 6959.
27. Prokopiou S, Barbarroux L, Bernard S, Mafille J, Leverrier Y, et al. (2014) Multiscale Modeling of the Early CD8 T-Cell Immune Response in Lymph Nodes: An Integrative Study. Computation 2 (4): 159–181.
28. Kiparissides A, Kucherenko SS, Mantalaris A, Pistikopoulos EN (2009) Global Sensitivity Analysis Challenges in Biological Systems Modeling. Ind Eng Chem Res 48 (15): 7168–7180.
41. Takao K, Miyakawa T (2014) Genomic responses in mouse models greatly mimic human inflammatory diseases. Proc Natl Acad Sci: 1401965111–.
52. Schlag G, Redl H, Davies J, Vuuren CJJ, Smuts P (1993) Live Escherichia coli Sepsis Models in Baboons. Pathophysiology of Shock, Sepsis, and Organ Failure. Springer Berlin Heidelberg. pp. 1076–1107.
67. Swigon D (2012) Ensemble Modeling of Biological Systems. In: Alexandra V. Antoniouk , Melnik RVN, editors. Mathematics and Life Sciences. Walter de Gruyter. pp. 19–42.
71. Roberts G, Gelman A, Gilks W (1997) Weak convergence and optimal scaling of random walk Metropolis algorithms. Ann Appl Probab 7 (1): 110–120.
72. Gelman A, Rubin DB (1992) lnference from Iterative Simulation Using Multiple Sequences. Stat Sci 7 (4): 457–472.
73. Brooks S, Gelman A (1998) General methods for monitoring convergence of iterative simulations. J Comput Graph Stat 7 (4): 434–455.
78. Hall M, Frank E, Holmes G (2009) The WEKA data mining software: an update. ACM SIGKDD Explor 11 (1): 10–18.
Is the Subject Area "Tempering" applicable to this article?


The 2015 Sports Illustrated Swimsuit Issue has been revealed and model Hannah Davis is the lucky lady chosen to grace the cover.
The 24-year-old Caribbean-born model poses suggestively in a black-and-white print bikini on the cover of the issue, one of the most coveted jobs in the modeling industry. While it's Davis' third time appearing in the Swimsuit Issue, she was thrilled to be selected as this years cover girl.
"I've always enjoyed the whole Swimsuit experience, and said that anything extra—a little square on the cover or anything like that—was a bonus," Davis told SI. "But still, this was my dream."
Davis didn't find out she was the cover until Tuesday, when SINow surprised her with a prank reveal.
"I told my mom there was no way I'd get the cover," the stunned model admitted. "I told her 'They do beaches for covers and I'm on a farm. There's no way. It's not possible.'"
Jimmy Fallon also revealed the cover on The Tonight Show on Wednesday.
Prior to the reveal, Jimmy made a joke about the Swimsuit Issue on Twitter.
Check out plus-size model Ashley Graham rocking a tiny bikini in the Sports Illustrated Swimsuit Issue!


Put the hurt in plastic garbage bags.
Tie it tight and shut your eyes.
No more eye tears. No more bag tears.
Be gentle with the grief as it is as fragile as dust bunnies.
the genius of Samuel R. Delany.
staying woke AF as pillow talk to each other.
Where did all this intimacy come from?
How much dead skin cells can I possibly shed?
Don't shut out the parts that ache.
Dale tiempo al tiempo. Diosito dijo que no era para ti.
The nostalgia swims heavy in the air like the fragrant Pine-Sol bucket.
There's nothing to say like there's nothing to make the floor dry faster.
very much like the four chambers of your heart.


text:
Q: Compute $P(2\leq x\leq 8)$ with Poisson distribution and $\lambda=7.2$ Compute $P(2\leq x\leq 8)$ with Poisson distribution and $\lambda=7.2$
My attempt:
I need calculate this using $R$. then
I use this:
> ppois(8,7.2, lower.tail = FALSE) - ppois(2,7.2,lower.tail = TRUE)

Is correct this? I'm a little confused here.
Other question: I need calculate 75 percentil of this distribution but i don't have idea of how solve this. Can someone help me?
In this case i think could be using qpois command but i don't sure.

A: That is not correct: Your inequality is inclusive of $X=2$ so you should not subtract the probability of this value in your calculation.  You can calculate the desired probability either by generating each of the individual mass-function values and summing them:
POIS <- dpois(2:8, lambda = 7.2)
PROB <- sum(POIS);
PROB;

[1] 0.6965463

or by taking the different of the cumulative distribution value, but removing the values below $X=2$:
PROB <- ppois(8, lambda = 7.2) - ppois(1, lambda = 7.2);
PROB;

[1] 0.6965463

redpajama_set_name: RedPajamaStackExchange


Welcome to Farmhouse Friends! (I mistakenly published this too early, everyone's post will be live tonight at 7pm!) Sorry!!
I've got an easy DIY for you today.
It's a pretty Summer Door Basket.
I bought this basket on Nantucket a few years ago for my mom.
She gave it back to me to use, thanks, mom!
I purchased three white geranium bunches, two white pom flowers bunches, one spool of burlap ribbon and one package of floral foam from the Dollar Tree.
First, I cut the blooms off the larger bunches. I used a wire cutter but if you don't have one you can bend the stems back and forth and they will break off.
I added them to the basket until I was happy with the arrangement.
I added in the white pom flowers.
I wrapped the basket with twine a few times and then added a burlap bow to the twine. I didn't want to glue the bow right to the basket.
I'm so happy with the way it turned out, it looks summery and happy!
Now let's see what the rest of our Best of Farmhouse Friends Team! has come up with! Sharing at these link parties!
What a sweet little summer basket! Pinned!
This is a perfect summer piece for your door or anywhere in your home that you choose to hang it. I like the addition of the bow.
So cute Susan, I love the idea of using the basket vs. a wreath! Great idea! Pinning!
Thank you Stacey! I have a thing for baskets!
Hi Paula!! I'm not even sure where it will end up!
Thank you Cindy!! :) blessings to you too!!
Tammy, thank you! I like to change it up so it's a nice change from a wreath!
Adorable and easy- just my thing! I love baskets of flowes, they are so cheerful.
Adorable summery basket, Susan! Love the white flowers and touch of burlap! Good job!
What a simple and charming project, Susan! I need to find a basket like this for our door!
What a beautiful idea for a welcome greeting. Perfect and fresh.
Thank you be great! Thank you Jess!!


text:
MEMFix Lessons
Build it and they will learn: lasting lessons from temporary MEMFix projects
Oct 14, 2014 | High Ground News
High Ground takes a look at the roots of the tactical urbanism movement in Memphis, beginning with the surprising success of Broad Avenue. With the support of adaptive city leadership and invigorated neighborhood stakeholders, each MEMFix has offered unique hands-on lessons.
"'Our goal for the last five years has not only been to redevelop the building, but also to build community. Part of that is putting Crosstown as a neighborhood back on the mental map of Memphians,' Richardson, an associate professor at the University of Memphis, said. 'To be able to bring that many people to the neighborhood in a single day, I can't praise the Mayor's Innovation Delivery Team enough for organizing it, their vision and the creativity they put forth.'"
Smart City Initiative Seeks to Improve Public Problems
Memphis Medical District Collaborative: Catalyzing Change on a Community Level
Innovate Memphis pushes to revamp Memphis bus system from the ground up

redpajama_set_name: RedPajamaCommonCrawl


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redpajama_set_name: RedPajamaGithub


Well over one year into his presidency, Donald Trump on Sunday blamed former President Barack Obama for the latest gas attack in Syria that resulted in the deaths of dozens of women and children.
Following a week in which the President insisted the U.S. end involvement in Syria, pro-government forces and their allies attacked Douma, the last remaining rebel stronghold near the Syrian capital.
Trump was late to criticize the al-Assad government on Sunday morning, choosing instead to launch a broadside at former Secretary of State Hillary Clinton and the Washington Post, but when he did, he included, Obama.
"Many dead, including women and children, in mindless CHEMICAL attack in Syria. Area of atrocity is in lockdown and encircled by Syrian Army, making it completely inaccessible to outside world. President Putin, Russia and Iran are responsible for backing Animal Assad. Big price to pay," Trump tweeted.
This gas attack was the second since Trump became President and he has done little about Syria in the intervening year.


text:
NourishKC
#LetsNourishKC
aka NourishKC | Kansas City, MO | http://nourishkc.org
NourishKC works collaboratively to innovate systemic changes in Greater Kansas City's emergency food services.
Sue Moore Fenske
Kansas City, MO 64111 USA
Show more contact info
Email contact available with a Pro subscription
International Address
Donation Payable
Legal name of organization: NourishKC
EIN for payable organization: 43-1525298
Episcopal Social Services
Food Service, Free Food Distribution Programs (K30)
Employment Training (J22)
Food Banks, Food Pantries (K31)
This organization is not required to file an annual return with the IRS because it is a religious organization.
SOURCE: Self-reported by organization
Too many people in our community do not have adequate access to food on a regular basis.
Kansas City Community Kitchen (KCCK)
Our community kitchen provides a hot, nutritionally balanced lunch every Monday through Friday, even holidays. The kitchen is open to anyone who comes, primarily to be a resource for those that have low or no income so that their limited resources might be used elsewhere. Food is prepared fresh, on-site daily by staff, culinary trainees and volunteers. KCCK also prepares meals to be delivered to partner organizations. This service is meant for partner service agencies that don't have the capacity to prepare their own food. In total, the kitchen provides more than 500 meals every weekday.
Population(s) Served
Economically disadvantaged people
Culinary Training Program
NourishKC's Culinary Skills Training is a 8-week intensive, entry-level program that provides basic culinary skills, job training, and hands-on experience in the food service industry. Emphasis is placed on food safety, basic food preparation, and professionalism.
Unemployed people
Food Rescue Program
Food rescue is the practice of recovering perfectly edible food that would otherwise end up in landfills from places such as farms, food distributors, grocery stores, produce markets, or restaurants and distributing it to local emergency food programs. NourishKC's Food Rescue Program is essential to providing balanced, nutritious meals at Kansas City Community Kitchen and assisting local pantries with access to fresh produce and shelf stable items on a weekly basis.
Affiliations & memberships
Nonprofit Connect of Greater Kansas City 2017
Volunteers serve as our "restaurant" staff, including beverage station, bussers, host stand and wait staff.
How does this organization measure their results? It's a hard question but an important one.
Evaluation documents
Download evaluation reports
Number of volunteers
This metric is no longer tracked.
Totals By Year
Social and economic status
Related Program
Type of Metric
Input - describing resources we use
Direction of Success
Holding steady
Context Notes
2015 & 2016 are estimates. In 2017 we noted the number of volunteer shifts. In 2018 we started using a new online management system and noted the number of registrations.
Number of meals provided
Adults, Children and youth
Output - describing our activities and reach
Total meals served through Kansas City Community Kitchen (includes hot lunches served in the dining room as well as meals to local partners serving throughout the week).
Goals & Strategy
Learn about the organization's key goals, strategies, capabilities, and progress.
Charting impact
Four powerful questions that require reflection about what really matters - results.
What is the organization aiming to accomplish?
NourishKC is striving to end food insecurity while promoting healthy food access every day. Our KCCK serves more than a warm meal, it provides a sense of community, consistent structure, and acknowledges the value of each person through our Dining with Dignity approach. NourishKC has strong relationships with our core volunteers, as many have been a part of KCCK efforts for years. We coach our volunteers to provide individual guest services and consistent kitchen functions so that guests feel valued while enjoying a healthy meal. Through community supports, volunteers, our Board of Directors, and donors NourishKC will continue to collaborate with other food access partners to address systemic food insecurity in the metro area.
What are the organization's key strategies for making this happen?
Our community kitchen currently serves lunch 5 days a week. Meals are served restaurant-style with guests getting a choice of entree and sides, being served by volunteer "wait staff" and being asked what they like or don't like. We eventually want to expand that program to 7 days a week in more a community diner/restaurant environment. We'd eventually like to see this become a network of "pantries" that feel more like a neighborhood corner store with strategic locations all over the metro. The Board of Directors is exploring ways to advance our culinary training program in 2020, as we suspended its efforts for 2019. The staff and board are also strategizing towards longer term goals through fundraising, infrastructure, policies, and sustainability to serve Kansas City area beyond 2020.
What are the organization's capabilities for doing this?
NourishKC has a team of 7 staff members devoted to various aspects of operations and program management. Our community kitchen is staffed by people with experience in restaurants and other commercial kitchens, and administrative staff have years of experience in their respective fields, from accounting to program management. The Board of Directors has a wide array of expertise to oversee the impact of established goals while adapting to the community needs based on organizational capacity. Our staff and board members have been fortunate to attend sessions at the Kansas Leadership Center during the past two years to learn active leadership through coaching and training. This learning opportunity has guided the Board and staff to adjust its daily efforts towards forward movement. Perhaps our greatest strength is our willingness and ability to build relationships with other organizations and collaboratively work on things beyond what any one of us is able to do on our own. Whole Food, Farm to Market Bread and other local companies donate food to us on a regular basis for use in our community kitchen, but then other companies like Harrah's, Citi, BlueScope Steel, Bayer, Cargill and KCPD send groups of volunteers on a regular basis so that our guests are served in a way that offers dignity. Another deep capacity of NourishKC is PEOPLE. The historic and new networks of volunteers is the breathe that keeps NourishKC feeding 400 people daily. The Board and staff are working to recruit more corporate, small business, and civic groups to learn how two hours of time truly impact a hungry person. Volunteer appreciation, regular communication, group incentives, and other supports are being developed for the Kansas City Community Kitchen's long-term success.
What have they accomplished so far and what's next?
This year NourishKC is focusing on transition processes and rebuilding measures for the Kansas City Community Kitchen while strategizing long-term programs for 2020. As noted by our Board of Directors, we are focusing our fundraising efforts to make headwinds to our sustainability and impact. Our working board and thousands of volunteers make every effort to assist in getting nutritious food to Kansas City community members.
Mark Galus
Terri Curran
Hallmark Cards (former)
Andrew Ehrlich
Geoff Parker
Retired, George K. Baum & Company
Jim Cummins
Deacon of Episcopal Church
Joselyn Pfliegier
Nancy LaPorta
Black & Veatch
Julie Stoetzer
Jennifer Rule
Community Volunteer
Julia Higgerson
Catalent Pharma Solution
Lindsay Harmon
Galus Legal LLC
Pierre Yancy
ThinkTank Solutions
Gar Demo
Saint Thomas Episcopal Church
Board leadership practices
GuideStar worked with BoardSource, the national leader in nonprofit board leadership and governance, to create this section.
Board orientation and education
Does the board conduct a formal orientation for new board members and require all board members to sign a written agreement regarding their roles, responsibilities, and expectations? Yes
CEO oversight
Has the board conducted a formal, written assessment of the chief executive within the past year ? Yes
Ethics and transparency
Have the board and senior staff reviewed the conflict-of-interest policy and completed and signed disclosure statements in the past year? Yes
Board composition
Does the board ensure an inclusive board member recruitment process that results in diversity of thought and leadership? Yes
Has the board conducted a formal, written self-assessment of its performance within the past three years? Yes
Organizational demographics
SOURCE: Self-reported; last updated 09/23/2021
Who works and leads organizations that serve our diverse communities? GuideStar partnered on this section with CHANGE Philanthropy and Equity in the Center.
The organization's leader identifies as:
White/Caucasian/European
Email contact information
Financial statements for 2020, 2019, 2018, ,
Letter of Determination
Board of Directors data for 2021


Heart of the West was written by Penelope Williamson. Heart of the West was published by Signet Book. Subjects of Heart of the West include Fiction, General, Historical fiction, and Modern fiction.
About Penelope Williamson (Author) : Penelope Williamson is a published author. Some of the published credits of Penelope Williamson include Wages of Sin.


Shelly is a Portfolio Manager with expertise in strategic wealth management. She has over 20 years of investment experience, helping affluent clients build, preserve and transition wealth. She manages her clients' financial resources by considering not only their fiscal situation, but also their non-financial needs and priorities. Taking the time to understand these priorities, she forms a cohesive and effective wealth management strategy for her clients.
Recognizing that a financial plan is constantly evolving, Shelly provides a full range of financial strategies relevant to different life stages. Her business focuses on advising families, entrepreneurs, as well as not-for-profit organizations and corporations with tailored financial solutions.
Since 2012, she has kept clients informed with her blog, per$pectives, which includes timely issues and topics.
Shelly's career with Odlum Brown began in 1996, after five years with the Vancouver Stock Exchange. She is a Portfolio Manager and holds the Certified International Wealth Manager (CIWM) designation, the industry-recognized standard for wealth management services for affluent individuals.
Shelly is active in the direction of the firm as a Vice President, a member of the firm's Board of Directors and Retail Sales Advisory Team (as past Co-Chair).
In addition to her Bachelor's Degree from Simon Fraser University, Shelly is a Fellow of the Canadian Securities Institute (FCSI), the highest designation granted by the Canadian Securities Institute. She has been active in the industry as a past member of FCSI's National Board of Directors and participated on the Board's Ethics Sub-Committee. In 2014, Shelly received the Chartered Financial Divorce Specialist designation, equipping her with the knowledge and tools to provide an objective assessment regarding financial settlement scenarios for matters relating to separation and divorce. In 2017, Shelly successfully completed the Certificate in Estate Planning and Trust Strategy.
Dedicated to enhancing the professional development of advisors, Shelly offers her knowledge and experience as a mentor to new advisors. In 2008, she formalized this commitment by forming STM Wealth Management, with colleagues Tannis Pratt and Mary MacDonald.
Making a difference in the lives of others has always mattered to Shelly. She has given her time and resources to a variety of charities and organizations. For 15 years, she led the firm's employee campaign for the United Way of the Lower Mainland and helped the Minerva Foundation get off the ground. Shelly also continues to participate in educational outreach programs through Junior Achievement of Canada. Inspired by the Me to We initiatives, she recently travelled to Kenya and Ecuador, has made a personal and financial commitment to the WE organization and has been a Patron Family for We Day celebrations in Vancouver since 2014. In October 2017, Shelly and her family's efforts were formally recognized by the WE organization and Canadian Living Magazine as a WE Family Award Recipient.
As an SFU Alumna, Shelly contributes back to the university as a member of its Business Board of Advisors, as a guest speaker for the Finance Club and as a sponsor of the SFU Annual Golf tournament benefitting athletes with scholarships and golf programming.
Shelly shares a passion for sports with her family. When she is not at the office, Shelly and her husband are actively supporting their daughter who figures skates competitively and their son who golfs.


text:
Q: How to have Bootstrap's scss variables globally in Angular without importing theme every time in each component? I know there is a way to use bootstrap's scss variables in angular by importing the _variables file in each component's scss file and then start using that variables and there is lots of questions answered with this approach.
But I think this way is not a good way. Is there another way to import variables file or whole bootstrap.scss file to use mixins and variables without importing necessories each time in each component style file?

*

*I am using angular-cli v1.7.4

A: This is not possible. Each component style is compiled separately.
https://github.com/angular/angular-cli/issues/3700
What you can do is specify the stylePreprocessorOptions in .angular-cli.json file so that you can import variables like
@import 'variables';

Instead of something like
@import '../styles/_variables.scss';

It's just more convenient, but you still have to include it in each component scss file


text:
SAILOR'S GRAVE BREWING
Gippsland, Victoria
"We might be in the middle of nowhere, but there is an absolute bounty out here," says Chris Moore, one half of Sailor's Grave. He's talking about the nettles, mallow and milk thistle that grows in the paddocks near their Orbost brewery in East Gippsland; he and his wife, Gabrielle, pick them and use them in their beers.
"There are endless inspirations around here," he continues. "Sometimes, the brief we give ourselves will be to make a beer that smells like a hay shed after a cutting. We take literal and emotional inspiration from the area. If there's blueberries growing, we'll pick them and put them in a beer."
Chris and Gab have a background in food – they used to own the Commons Local Eating House in Sydney – so although they may get creative with their brews, there's nothing novelty about what they make. They are about drinkability first and foremost.
"There is a trend sometimes in the brew world that bigger is better," says Chris. "But we're more about balance and subtlety, and layers of flavour, and the story of the ingredients rather than big and hoppy and high alcohol."
The core range of beers includes the Down She Gose, Drowned Man IPA, and the Southern Right Ale. Sailor's Grave also brews a range of seasonal beers (like a mandarin Berliner or grapefruit and marigold saison), and in the same way they forage locally for new ingredients, Chris and Gab also collaborate with local wineries and other producers on special release beers (they made a Pinot beer with Lightfoot & Sons in 2017).
If you don't include the years of planning and research trips, Sailor's Grave has only been operating for less than two years. Chris and Gab brew in an abandoned, 1893-era butter factory, which still has much of its original fittings including beautiful blue tiles.
They named their label after a cove at nearby Cape Conran. Sailor's Grave is a rocky, wild coast, and many ships have been wrecked and sailors' lives lost there. There's also rumoured to be some graves in the dunes. Gab's family had property there when she was growing up, so it made sense to return and set up the brewery.
As the brewery is so remote, there is no tasting room or similar set up for drop-ins. The Moores are always willing to show interested people around and set up tastings by appointment, however. They also host regular events on the property, like the Deep Winter Festival they hosted over three days in June 2018.
Follow them on Instagram and Facebook for updates.
7 Forest Rd, Orbost 3888
sailorsgravebrewing.com
LIKE THIS? Then check out the rest of our Gippsland adventures below!
GIPPSLAND – Victoria's Dark Horse
WILLIAM DOWNIE
Gippsland, Vic
GIPPSLANDIA
LIGHTFOOT & SONS
BASS RIVER
PROM COUNTRY CHEESE
LOCH BREWERY & DISTILLERY
TAMSIN CARVAN
THE WINE FARM
PATRICK SULLIVAN
ONANNON
DIRTY THREE WINES
CANNIBAL CREEK


Betty has been an activist for most of her 97 years.
A veteran campaigner for peace and women's rights, she has been an inspiration to successive generations. Now aged 97, we look back with her at her upbringing and the struggles that formed her political character. With contributions from friends and fellow campaigners this is sure to be an inspirational evening as we celebrate a lifetime of political commitment.
Tickets £2 (proceeds to Gaza Women's Educational Fund).
All seats for this event are sold. There will be ten standing only tickets available at the door.


Due to improvement in technology, the education sector has benefited since students can learn through the digital platform. Most learning institutions have embraced the use of computers and tablet to aid in the learning process. Before the devices are used in the classrooms, the teachers and students should be trained in how to use them . The laptops and the tablets require internet connectivity such as Wi-Fi before they can operate. Some of the advantages of using ebooks are listed below.
After downloading the specific e-books from the different reading devices, deliveries are made instantly. E books offer convenience to the readers since they do bit have to move from one bookshop searching for a specific book. Since the purchases are done through the digital platform, people can buy a variety of books in the comfort of their homes, schools or workplaces. E books can be downloaded on different devices which makes it easy for people to purchase the devices that they can afford. The e-book platform offers safety for the books so people do not worry about losing the books. E books do not require replacement like the printed version that may get lost or be subjected to tear. See more details at this website https://www.dictionary.com/browse/ebook about eBook.
With the introduction of e-books, the ecosystem is not affected since no trees are required in the manufacturing of the books. This is not the same scenario of with printed version which requires the trees in the manufacturing process causing damages to the trees. E book is convenient since people can download specific information without buying the book as in the case of the printed version. One will not be required to set aside a particular storage area such as the libraries for e-books . When one purchase s the printed version, they must have a storage facility for the books so that they do not get damaged. Availability of the computers and other storage devices enables users to store many books. Know more here!
When one carries e-books, they will not feel any weight. When people carry the printed version, they are bound to get tired due to the weight they have. E books are never out of stock like the printed version may force people to walk around in different bookshops for the search. Student sand people who want information from e-books are guaranteed of a smooth learning process. E book platform is cost effective compared to the printed version which requires a lot of money in purchasing them. Different bookshops have their own rate of the books and this may be expensive to people who want several books. The schools should provide their students with the same devices so that uniformity is maintained during the learning process, click for more details!


This sea creature assortment is perfect for sending a little message from the Chesapeake Bay or an invitation to your beach home. Hand engraved in fine detail, the assortment contains our Lobster, Crab & Octopus designs - all with matching lined envelopes. Blank inside, each note provides plenty of room for your hand-written words. Three of each design are included.
Designed to be versatile, assorted boxed stationery makes an ideal hostess gift or little token of gratitude!


Residential and commercial battery backup ensures that a property's gate system is secure during a power outage and capable of still operating so you're not shut out unnecessarily, but valuables and residences are still kept secure. Using a DC battery backup is also good for residences with a security gate, helping homeowners feel more secure. Since some acts of vandalism or burglary happen during lengthy power disruptions, homeowners enjoy the additional protection. At PSSStore.net, we carry battery backups from top gate security brands such as DoorKing and the LiftMaster battery backup.
Our gate operator replacement batteries are one of the most important accessories you will need for your gate. At PSS Store, we have affordable and quality replacements for a wide variety of gate brands. It is important to make sure that your gate system always has functional batteries. Some of the systems require only a single battery, while others may operate on two batteries. It is important to know exactly what your system's battery needs are before you replace them, but our LiftMaster battery replacement model can several other gate operator models, which will give you greater peace of mind about having the right battery. We offer enough different battery products to ensure that you will find what you need. Browse our selection to get started.
If you're looking for a battery backup system the PSS Store has what you need: solar battery gate openers, replacement batteries, an automatic gate battery and more. These backup systems provide everything you need to supply power to your gate when the primary AC power fails.
Don't see a backup battery system for your gate? Give us a call at 1-800-676-4909 and one of our security experts can help you locate the battery that will work best for your gate. Perimeter Security Systems has been installing, repairing and selling security gates for more than 40 years. We are leaders in our industry, and we're up-to-date on all the latest offerings from the top manufacturers.


Chris and Julie Bullen brought a group of Canadian neighbors to Northern Michigan for the Water Wonderland Chapter's "August Adventure" which involved some classic boating activities during the week prior to the Hessel Boat Show. The group arrived in the Northern Lower Peninsula Monday evening, August 5, for boating there on Tuesday and Wednesday with Bil and Karen Ballard and Jim and Wendy Mersman as heir hosts.
Thursday morning the group toured Van Dam Custom Boats in Boyne City, and then drove to the Les Cheneaux Islands that afternoon to visit the Great Lakes Boat Building School. In the Upper Penninsula. they were hosted by Lynda and Gerry VandeVusse, which included a meet and greet get together at Gerry and Lynda's home on the north shore of Sheppard Bay in Cedarville on Thursday evening.
On Friday the group participated in the Water Wonderland Chapter's Poker Run and Annual Picnic, and then on Saturday they attended the 37th Annual Les Cheneaux Islands Antique Wooden Boat Show.
At the show, Rich and Linda Hughes of TSACBA received three major awards. The Hughes Aqua Velvet, a 1968 22ft Greavette Executive, was awarded First in her Class, Second Best of Show, and the prestigious major award for the show, The Bronson Family Award for Best Craftsman.
At the same show, Chris and Julie Bullens Gatsby, a 1947 22ft W. J. Johnson Triple Runabout, was awarded Second Place for Best Runabout. They are members of both the Toronto and Water Wonderland Chapters of ACBS, as well as members of the TSACBA. Chris is a Past President of the Toronto Chapter.
Also travelling to Michigan were TSACBA members Bryan and Kathy Rhodes. Kathy is the current President of the Toronto Chaper. They were accompanied by TSACBA Members Jim and Merridy Watt (Jim is Past President of TSACBA) and of course Rich and Linda Hughes (Rich is TSACBA's current president). As well, two TSACBA distant members Norm and Kathy Kitching from Los Altos, California, joined the group.
Along with the Hughes and Bullens boats, the Watts brought their 1950 15ft Heron by Link Manufacturing of Gananoque Ontario. The Kitchings were planning to bring a boat but unfortunately last minute problems prevented them from doing so.
TSACBA members can enjoy the trip by viewing the video of our members' adventures in Michigan.
Rich Hughes provided the following pictures from the group's Michigan "adventure."
Leaving Sarnia for Port Huron, Michigan and The Boyne Mountain Lodge, home for the next three nights.
Chris and Julie Bullen and Bryan and Kathy Rhodes in "Gatsby" and boating down the Crooked River.
The "Clam Lock" near Alanson and Jim Watt takes the wheel of "Aqua Velvet" for a sunset cruiser.
Sunset on Walloon Lake and our commander, Chris Bullen, leads the fleet.
Stopping for lunch on Torch Lake and the famous aqua waters of Torch Lake.
Stopping at the sandbar for afternoon tea and Bryan Rhodes testing the water.
Visit to VanDam Custom Boats and Julie, Linda and Kathy eying up some VanDam jewellery.
Rich's favorite boat, the "Susan C" and Friday morning poker run in the Les Cheneaux Islands.
The poker run lunch stop and Norm Kitching relaxing after driving all the way from California.
Kathy Kitching enjoying a boat ride with Jim and Merridy Watt and Rich and Linda Hughes "Aqua Velvet" at the Hessel Boat Show.
Jim Watt with his Link boat at the Hessel Boat Show and Chris and Julie Bullen's "Gatsby" at the Hessel Boat show.
On the way home back to Canada via Sault Ste. Marie.


If it's been a while since you've seen a dentist, you're not alone. About one third of people in the U.S. don't see a dentist yearly, according to the American Dental Association (ADA) Mouth Healthy site. But booking this appointment is one of the most important things you can do when looking after your teeth. According to the ADA, some conditions – such as sensitivity in the teeth or bleeding gums – are sure signs that it's time to see a dentist. Even if your teeth look and feel fine, enter a reminder in your phone or calendar for January 1 so that you can call your dentist on January 2 for an appointment.
Brushing your teeth twice a day isn't enough to keep plaque from building up on your teeth, or to completely remove bits of food from your mouth. To take the best care of your teeth, you need to floss too. If you're not in the habit of flossing, the new year is a great time to start.
One way to make it easier to remember is putting a container of floss on top of or directly next to your Colgate Total® Clean Mint Toothpaste. Position the container so that you have to touch it when taking your toothpaste out of the drawer or cabinet. Stash another container of floss in your purse or desk drawer at work, so that you can floss on the go if you forget to do it at home.
Smoking doubles your risk for gum disease, according to the Centers for Disease Control and Prevention (CDC), and is linked to a host of other health issues. Pick a date to give up the habit, get rid of all the tobacco products from your home and solicit the support of your friends and family to help you quit. There will be cravings along the way, so it's important to find a healthy activity to engage in when a craving kicks in. Feel free to see your general practitioner if you struggle to curb the addiction by yourself.
When you cut back on sugar, resolve to add more orally healthy foods to your diet to solidify your diet's benefit to your teeth. Dairy products, which are high in calcium, are great for your teeth, as are fibrous foods that call up saliva and scrub away plaque and other food bits, according to Delta Dental.
Making your new year's resolutions as easy as possible to stick with will help you keep them. Take things one step at a time, and if you forget to floss one day or eat a big piece of caramel the next, don't give up. Remember that there's always tomorrow!