Simulation Comparison of Methods to Estimate Confidence Intervals of the Mitigated Fraction

In the area of veterinary medicine, efficacy studies are conducted to support licensure of vaccines. Such studies are typically designed to assess a vaccine\u27s ability to prevent or mitigate clinical disease. For example, reduction of duration/severity of clinical signs or the severity of lung lesions are often considered as primary or secondary criteria of success. Studies designed to measure efficacy typically utilize two or more treatment groups and often use blocking structures to accommodate animal housing or litter related effects. When the criteria of interest are continuous or ordinal variables, as is the case with the above measurements, the mitigated fraction (MF) is often used to quantify a vaccine effect. One common approach involves determining the confidence interval for the MF using a bootstrap procedure. For data arising from studies with a blocking structure, there are two bootstrap procedures that are often used. The first resamples the blocks with replacement (randomized cluster bootstrap). The second resamples the blocks and the subjects within blocks, both with replacement (two-stage bootstrap). In addition to the bootstrap procedures, an asymptotic estimate of the variance of the MF can be calculated and used to construct a confidence interval. With three potential methods, it is of interest to determine coverage related to the associated intervals using study designs commonly used for in efficacy studies. In addition, coverage was assessed in situations with and without a treatment effect. Using parameter estimates obtained from the data in which lung lesions were measured, we conducted a simulation experiment estimating the MF and confidence interval using each method described above. The results from this simulation study suggest the bootstrap procedures perform poorly when no treatment effect is present, while the confidence interval estimated using the asymptotic variance performs well. However, none of the methods perform particularly well in the presence of a treatment effect

A Dynamic Model of the Opioid Drug Epidemic with Implications for Policy

Background: The U.S. opioid epidemic has caused substantial harm for over 20 years. Policy interventions have had limited impact and sometimes backfired. Experts recommend a systems modeling approach to address the complexities of opioid policymaking. Objectives: Develop a system dynamics simulation model that reflects the complexities and can anticipate intended and unintended intervention effects. Methods: The model was developed from literature review and data gathering. Its outputs, starting 1990, were compared against 12 historical time series. Illustrative interventions were simulated for 2020-2030: reducing prescription dosage by 20%, cutting diversion by 30%, increasing addiction treatment from 45% to 65%, and increasing lay naloxone use from 4% to 20%. Sensitivity testing was performed to determine effects of uncertainties. No human subjects were studied. Results: The model fits historical data well with error percentage averaging 9% across 201 data points. Interventions to reduce dosage and diversion reduce the number of persons with opioid use disorder (PWOUD) by 11% and 16%, respectively, but each reduces overdoses by only 1%. Boosting treatment reduces overdoses by 3% but increases PWOUD by 1%. Expanding naloxone reduces overdose deaths by 12% but increases PWOUD by 2% and overdoses by 3%. Combining all four interventions reduces PWOUD by 24%, overdoses by 4%, and deaths by 18%. Uncertainties may affect these numerical results, but policy findings are unchanged.Conclusion: No single intervention significantly reduces both PWOUD and overdose deaths, but a combination strategy can do so. Entering the 2020s, only protective measures like naloxone expansion could significantly reduce overdose deaths

Creating Clinically Useful \u3ci\u3eIn Silico\u3c/i\u3e Models of Intracranial Pressure Dynamics

To create clinically useful computer simulation models of intracranial pressure (ICP) dynamics by using prospective clinical data to estimate subject-specific physiologic parameters

A Hybrid Simulation Model for Studying Acute Inflammatory Response

The modeling of complex biological systems presents a significant challenge. Central to this challenge is striking a balance between the degree of abstraction required to facilitate analysis and understanding, and the degree of comprehensiveness required for fidelity of the model to its reference-system. It is likely necessary to utilize multiple modeling methods in order to achieve this balance. Our research created a hybrid simulation model by melding an agent-based model of acute local infection with a system dynamics model that reflects key systemic properties. The agent based model was originally developed to simulate global inflammation in response to injury or infection, and has been used to simulate clinical drug trials. The long term objective is to develop models than can be scaled up to represent organ and system level phenomena such as multiple organ failure associated with severe sepsis. The work described in this paper is an initial proof of concept of the ability to combine these two modeling methods into a hybrid model, the type of which will almost certainly be needed to accomplish the ultimate objective of comprehensive in silico research platforms

A Systems Approach to Stress, Stressors and Resilience in Humans

The paper focuses on the biology of stress and resilience and their biomarkers in humans from the system science perspective. A stressor pushes the physiological system away from its baseline state towards a lower utility state. The physiological system may return towards the original state in one attractor basin but may be shifted to a state in another, lower utility attractor basin. While some physiological changes induced by stressors may benefit health, there is often a chronic wear and tear cost due to implementing changes to enable the return of the system to its baseline state and maintain itself in the high utility baseline attractor basin following repeated perturbations. This cost, also called allostatic load, is the utility reduction associated with both a change in state and with alterations in the attractor basin that affect system responses following future perturbations. This added cost can increase the time course of the return to baseline or the likelihood of moving into a different attractor basin following a perturbation. Opposite to this is the system’s resilience which influences its ability to return to the high utility attractor basin following a perturbation by increasing the likelihood and/or speed of returning to the baseline state following a stressor. This review paper is a qualitative systematic review; it covers areas most relevant for moving the stress and resilience field forward from a more quantitative and neuroscientific perspective

A Computer Model of Intracranial Pressure Dynamics During Traumatic Brain Injury that Explicitly Models Fluid Flows and Volumes

This report documents a computer model of intracranial pressure (ICP) dynamics that is used to evaluate clinical treatment options for elevated ICP during traumatic brain injury (TBI). The model uses fluid volumes as primary state variables and explicitly models fluid flows as well as the resistance, compliance, and pressure associated with each of the compartments (arteries and arterioles, capillary bed, veins, venous sinus, ventricles, and brain parenchyma). The model has been tested to assure that it reproduces a correct physiologic response to intra-and extra-parenchymal hemorrhage and edema, and to therapies directed at reducing ICP such as cerebral spinal fluid drainage, mannitol administration, head elevation, and mild hyperventilation. The model is able to replicate observed clinical behavior in many cases, including elevated ICP associated with severe cerebral edema, subdural hematoma, and cerebrospinal fluid blockage. The model also successfully reproduces tne cerebrovascular regulatory mechanisms that are activated during TBI in response to various abnormalities such as high or low systemic blood pressure. We conclude that incorporating fluid volumes and flows into a model of lCP dynamics significantly improved its clinical utility. Additional improvements are anticipated (or wil1 accrue or will result) as the specific mechanisms that modify cerebral compliance and autoregulation during TBI and elevated ICP are further delineated

Key Data Gaps for Understanding Trends in Prescription Opioid Analgesic Abuse and Diversion Among Chronic Pain Patients and Nonmedical Users

Population dynamics of medical and nonmedical prescription opioid usage and adverse outcomes were modeled. Critical parameter values were determined by their amount of influence on model behavior. Results suggest that closing these data gaps would help researchers to better identify ways to reduce the risk of adverse outcomes

Physics Design Requirements for the National Spherical Torus Experiment Liquid Lithium Divertor

Recent NSTX high power divertor experiments have shown significant and recurring benefits of solid lithium coatings on PFC's to the performance of divertor plasmas in both L- and H- mode confinement regimes heated by high-power neutral beams. The next step in this work is installation of a liquid lithium divertor (LLD) to achieve density control for inductionless current drive capability (e.g., about a 15-25% ne decrease from present highest non-inductionless fraction discharges which often evolve toward the density limit, ne/nGW~1), to enable ne scan capability (x2) in the H-mode, to test the ability to operate at significantly lower density for future ST-CTF reactor designs (e.g., ne/nGW = 0.25), and eventually to investigate high heat-flux power handling (10 MW/m2) with longpulse discharges (>1.5s). The first step (LLD-1) physics design encompasses the desired plasma requirements, the experimental capabilities and conditions, power handling, radial location, pumping capability, operating temperature, lithium filling, MHD forces, and diagnostics for control and characterization

TLR Tolerance Reduces IFN-Alpha Production Despite Plasmacytoid Dendritic Cell Expansion and Anti-Nuclear Antibodies in NZB Bicongenic Mice

Genetic loci on New Zealand Black (NZB) chromosomes 1 and 13 play a significant role in the development of lupus-like autoimmune disease. We have previously shown that C57BL/6 (B6) congenic mice with homozygous NZB chromosome 1 (B6.NZBc1) or 13 (B6.NZBc13) intervals develop anti-nuclear antibodies and mild glomerulonephritis (GN), together with increased T and B cell activation. Here, we produced B6.NZBc1c13 bicongenic mice with both intervals, and demonstrate several novel phenotypes including: marked plasmacytoid and myeloid dendritic cell expansion, and elevated IgA production. Despite these changes, only minor increases in anti-nuclear antibody production were seen, and the severity of GN was reduced as compared to B6.NZBc1 mice. Although bicongenic mice had increased levels of baff and tnf-α mRNA in their spleens, the levels of IFN-α-induced gene expression were reduced. Splenocytes from bicongenic mice also demonstrated reduced secretion of IFN-α following TLR stimulation in vitro. This reduction was not due to inhibition by TNF-α and IL-10, or regulation by other cellular populations. Because pDC in bicongenic mice are chronically exposed to nuclear antigen-containing immune complexes in vivo, we examined whether repeated stimulation of mouse pDC with TLR ligands leads to impaired IFN-α production, a phenomenon termed TLR tolerance. Bone marrow pDC from both B6 and bicongenic mice demonstrated markedly inhibited secretion of IFN-α following repeated stimulation with a TLR9 ligand. Our findings suggest that the expansion of pDC and production of anti-nuclear antibodies need not be associated with increased IFN-α production and severe kidney disease, revealing additional complexity in the regulation of autoimmunity in systemic lupus erythematosus

B Cell Activating Factor (BAFF) and T Cells Cooperate to Breach B Cell Tolerance in Lupus-Prone New Zealand Black (NZB) Mice

The presence of autoantibodies in New Zealand Black (NZB) mice suggests a B cell tolerance defect however the nature of this defect is unknown. To determine whether defects in B cell anergy contribute to the autoimmune phenotype in NZB mice, soluble hen egg lysozyme (sHEL) and anti-HEL Ig transgenes were bred onto the NZB background to generate double transgenic (dTg) mice. NZB dTg mice had elevated levels of anti-HEL antibodies, despite apparently normal B cell functional anergy in-vitro. NZB dTg B cells also demonstrated increased survival and abnormal entry into the follicular compartment following transfer into sHEL mice. Since this process is dependent on BAFF, BAFF serum and mRNA levels were assessed and were found to be significantly elevated in NZB dTg mice. Treatment of NZB sHEL recipient mice with TACI-Ig reduced NZB dTg B cell survival following adoptive transfer, confirming the role of BAFF in this process. Although NZB mice had modestly elevated BAFF, the enhanced NZB B cell survival response appeared to result from an altered response to BAFF. In contrast, T cell blockade had a minimal effect on B cell survival, but inhibited anti-HEL antibody production. The findings suggest that the modest BAFF elevations in NZB mice are sufficient to perturb B cell tolerance, particularly when acting in concert with B cell functional abnormalities and T cell help