scholarly journals Development of a dose–response model for Naegleria fowleri

2018 ◽  
Vol 17 (1) ◽  
pp. 63-71 ◽  
Author(s):  
Kara Dean ◽  
Mark H. Weir ◽  
Jade Mitchell
Keyword(s):  
Dose Response ◽  
Response Model ◽  
Naegleria Fowleri ◽  
Data Set ◽  
Response Models ◽  
Exposure Pathway ◽  
Accurate Dose ◽  
Plumbing Systems ◽  
Nægleria Fowleri ◽  
Measured Response

Abstract This study develops novel dose–response models for Naegleria fowleri from selected peer-reviewed experiments on the virulence based on the intranasal exposure pathway. One data set measured the response of mice intranasally inoculated with the amebae and the other study addressed the response of mice swimming in N. fowleri infected water. The measured response for both studies was death. All experimental data were best fit by the beta-Poisson dose–response model. The three swimming experiments could be pooled, and this is the final recommended model with an LD50 of 13,257 amebae. The results of this study provide a better estimate of the probability of the risk to N. fowleri exposure than the previous models developed based on an intravenous exposure. An accurate dose–response model is the first step in quantifying the risk of free-living amebae like N. fowleri, which pose risks in recreational environments and have been detected in drinking water and premise plumbing systems. A better understanding of this risk will allow for risk management that limits the ability for pathogen growth, proliferation, and exposure.

scholarly journals A generalized dose-response relationship for adenovirus infection and illness by exposure pathway

2016 ◽  
Vol 144 (16) ◽  
pp. 3461-3473 ◽  
Author(s):  
P. TEUNIS ◽  
J. SCHIJVEN ◽  
S. RUTJES
Keyword(s):  
Dose Response ◽  
Respiratory Illness ◽  
Response Model ◽  
Response Relationship ◽  
Limited Data ◽  
Dose Response Relationship ◽  
Oral Ingestion ◽  
Exposure Pathway ◽  
Inoculation Route ◽  
Account Variation

SUMMARYAdenoviruses are found everywhere in the environment, and cause various health problems including symptoms of enteric illness, and respiratory illness. Despite their significance to public health, few studies have addressed the health risks associated with exposure to adenovirus. Human challenge studies have been published for a few adenoviruses, which involved exposure through oral ingestion, inhalation, intranasal and intraocular droplet inoculation. Nothwithstanding the different symptoms resulting from such exposures, infection can be defined as colonization of a corresponding mucosa. A two-level dose-response model was developed to describe the distributions of infectivity and pathogenicity in various challenge studies of adenovirus, incorporating differences in inoculation route as shift in average infectivity and pathogenicity. This dose-response model can be used to make predictions for the infectivity of adenovirus, specific to any of the four studied inoculation methods. The generalized adenovirus dose-response relationship for infection and acute illness takes into account variation in infectivity and/or pathogenicity across adenovirus types, as well as uncertainty due to limited data.

scholarly journals Pharmacodynamic effect of bempedoic acid and statin combinations: predictions from a dose–response model

2021 ◽  
Author(s):  
Satyawan B Jadhav ◽  
Ryan L Crass ◽  
Sunny Chapel ◽  
Michael Kerschnitzki ◽  
William J Sasiela ◽  
...  
Keyword(s):  
Dose Response ◽  
Phase 1 ◽  
Lipid Lowering ◽  
Similar Degree ◽  
Lipid Lowering Therapy ◽  
Response Model ◽  
Atp Citrate Lyase ◽  
Pharmacodynamic Interaction ◽  
Response Models ◽  
Statin Dose

Abstract Aims Many patients are unable to achieve guideline-recommended LDL cholesterol (LDL-C) targets, despite taking maximally tolerated lipid-lowering therapy. Bempedoic acid, a competitive inhibitor of ATP citrate lyase, significantly lowers LDL-C with or without background statin therapy in diverse populations. Because pharmacodynamic interaction between statins and bempedoic acid is complex, a dose–response model was developed to predict LDL-C pharmacodynamics following administration of statins combined with bempedoic acid. Methods and results Bempedoic acid and statin dosing and LDL-C data were pooled from 14 phase 1–3 clinical studies. Dose–response models were developed for bempedoic acid monotherapy and bempedoic acid–statin combinations using previously published statin parameters. Simulations were performed using these models to predict change in LDL-C levels following treatment with bempedoic acid combined with clinically relevant doses of atorvastatin, rosuvastatin, simvastatin, and pravastatin. Dose–response models predicted that combining bempedoic acid with the lowest statin dose of commonly used statins would achieve a similar degree of LDL-C lowering as quadrupling that statin dose; for example, the predicted LDL-C lowering was 54% with atorvastatin 80 mg compared with 54% with atorvastatin 20 mg + bempedoic acid 180 mg, and 42% with simvastatin 40 mg compared with 46% with simvastatin 10 mg + bempedoic acid 180 mg. Conclusion These findings suggest bempedoic acid combined with lower statin doses offers similar LDL-C lowering compared with statin monotherapy at higher doses, potentially sparing patients requiring additional lipid-lowering therapies from the adverse events associated with higher statin doses.

scholarly journals A ready-to-use dose-response model of Campylobacter jejuni implemented in the FSKX-standard

2021 ◽  
Vol 2 ◽  
Author(s):  
Esther M. Sundermann ◽  
Maarten Nauta ◽  
Arno Swart
Keyword(s):  
Campylobacter Jejuni ◽  
Dose Response ◽  
Risk Assessments ◽  
Response Model ◽  
Response Models ◽  
Model Parameter ◽  
Parameter Values ◽  
Executable Model

Dose-response models are an important part of quantitative microbiological risk assessments. In this paper, we present a transparent and ready-to-use version of a published dose-response model that estimates the probability of infection and illness after the consumption of a meal that is contaminated with the pathogen Campylobacter jejuni. To this end, model and metadata are implemented in the fskx-standard. The model parameter values are based on data from a set of different studies on the infectivity and pathogenicity of Campylobacter jejuni. Both, challenge studies and outbreaks are considered, users can decide which of these is most suitable for their purpose. We present examples of results for typical ingested doses and demonstrate the utility of our ready-to-use model re-implementation by supplying an executable model embedded in this manuscript.

Risk Assessment for Fetal Toxicity

1985 ◽  
Vol 1 (4) ◽  
pp. 299-310 ◽  
Author(s):  
John Van Ryzin
Keyword(s):  
Risk Assessment ◽  
Toxic Effect ◽  
Dose Response ◽  
Risk Assessments ◽  
Control Group ◽  
Response Model ◽  
Statistical Research ◽  
Response Models ◽  
Fetal Toxicity ◽  
Using Data

This paper reviews the problem of performing risk assessments using data on fetal toxic effects. It briefly discusses the usual dose-response models and their inappropriateness for application to such data. The paper then considers tests for determining whether the fetal toxic effect is increased over that of the control group. Assuming an increase has been shown, the use of a fetal toxicity, dose-response model for risk assessment is discussed. The paper then applies these methods to data from an experiment using female mice mated with irradiated males. Finally, the paper discusses the need for further statistical research in this important area.

Assessing Juvenile Salmonid Response to Gas Supersaturation Using a General Multivariate Dose–Response Model

1986 ◽  
Vol 43 (9) ◽  
pp. 1694-1709 ◽  
Author(s):  
J. O. T. Jensen ◽  
J. Schnute ◽  
D. F. Alderdice
Keyword(s):  
Water Depth ◽  
Dose Response ◽  
Oncorhynchus Tshawytscha ◽  
Salmo Gairdneri ◽  
Fish Length ◽  
Response Model ◽  
Full Data ◽  
Data Set ◽  
Fish Size ◽  
New Device

Based on data compiled from the literature, we investigate the effects of excess total gas pressure (TGP%) on juvenile salmonids (chinook, Oncorhynchus tshawytscha; coho, O. kisutch; sockeye, O. nerka; and steelhead, Salmo gairdneri). Our study relates exposure time to 50% mortality (ET50) to TGP%, component levels of dissolved oxygen (O2%) and nitrogen (N2%), water depth, temperature, barometric pressure (BP), and fish size. We employ a new device, called a tabular histogram, for exploratory data analysis. We also formulate and test statistical hypotheses by applying the general multivariate dose–response model described in a companion paper (Can. J. Fish. Aquat. Sci. 43: 1684–1693). When modeled in response to TGP%, ET50 follows a typical exponential dose–response relationship. Based on our full data set, two ancillary factors, water depth and fish length, significantly improve the model's ability to explain variations in ET50. Furthermore, based on a smaller subset of the data, either of the factors O2% or N2% also improve the model fit significantly. For 50-d exposures, apparently "safe" levels of TGP% range from 103.8 to 114.8%, depending on associated factor levels of water depth and fish size.

scholarly journals Additive Dose Response Models: Defining Synergy

2018 ◽  
Author(s):  
Simone Lederer ◽  
Tjeerd M.H. Dijkstra ◽  
Tom Heskes
Keyword(s):  
High Throughput ◽  
Dose Response ◽  
Antagonistic Effect ◽  
Parametric Approach ◽  
Huge Amount ◽  
Response Models ◽  
Explicit Formulation ◽  
Measured Response ◽  
Loewe Additivity ◽  
Bliss Independence

AbstractIn synergy studies, one focuses on compound combinations that promise a synergistic or antagonistic effect. With the help of high-throughput techniques, a huge amount of compound combinations can be screened and filtered for suitable candidates for a more detailed analysis. Those promising candidates are chosen based on the deviance between a measured response and an expected non-interactive response. A non-interactive response is based on a principle of no interaction, such as Loewe Additivity [Loewe, 1928] or Bliss Independence [Bliss, 1939]. In Lederer et al. [2018a], an explicit formulation of the hitherto implicitly defined Loewe Additivity has been introduced, the so-called Explicit Mean Equation. In the current study we show that this Explicit Mean Equation outperforms the original implicit formulation of Loewe Additivity and Bliss Independence when measuring synergy in terms of the deviance between measured and expected response. Further, we show that a deviance based computation of synergy outper-forms a parametric approach. We show this on two datasets of compound combinations that are categorized into synergistic, non-interactive and antagonistic [Yadav et al., 2015, Cokol et al., 2011].

Efficacy of a combined system of copper and silver and free chlorine for inactivation of Naegleria fowleri amoebas in water

1995 ◽  
Vol 31 (5-6) ◽  
pp. 119-122 ◽  
Author(s):  
J. M. Cassells ◽  
M. T. Yahya ◽  
C. P. Gerba ◽  
J. B. Rose
Keyword(s):  
Synergistic Effect ◽  
Exposure Time ◽  
Silver Ions ◽  
Free Chlorine ◽  
Log10 Reduction ◽  
Naegleria Fowleri ◽  
Combined System ◽  
Water Ph ◽  
Nægleria Fowleri ◽  
Time Required

Electrolytically generated copper and silver ions (400:40 and 800:80 μg/l) were evaluated, separately and combined with 1.0 mg/l free chlorine, for their efficacy in reducing the viable numbers of Naegleria fowleri amoebas in water (pH 7.3 and 23-25°C). Inactivation rates (k = log10 reduction/min) and T99 values (exposure time required to achieve a 99% or a 2 log10 reduction) of the disinfectants were determined. Copper and silver alone, at ratio of 400:40 to 800:80 μg/l caused no significant inactivation of N. fowleri even after 72 hours of exposure (k = 0.00017 and 0.00013, respectively). Addition of 1.0 mg/l free chlorine to water which contained 400:40 or 800:80 μg/l copper and silver resulted in enhanced inactivation rates (k = 0.458 and 0.515, respectively) compared to either chlorine alone (k = 0.33) or the metals alone. Water containing 800:80 μg/l copper and silver with 1.0 mg/l chlorine showed a T99 value of 3.9 minutes, while chlorine alone showed a T99 of 6.1 minutes. Enhanced inactivation of N. fowleri by a combined system of free chlorine and copper and silver may be attributed to the different mechanism that each disinfectant utilizes in inactivating the amoebas, and may suggest a synergistic effect.

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