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Stittelaar K.J.,Viroclinics Biosciences | Veldhuis Kroeze E.J.B.,Viroclinics Biosciences | Veldhuis Kroeze E.J.B.,Erasmus Medical Center | Rudenko L.,2 Academy Pavlov Street | And 5 more authors.
Vaccine | Year: 2011

The advent of the H1N1 influenza pandemic (pH1N1) in 2009 triggered the rapid production of pandemic influenza vaccines, since seasonal influenza vaccines were expected and demonstrated not to provide significant cross-protection against the newly emerged pandemic virus. To increase vaccine production capacity and further evaluate the effectiveness of different candidate pandemic influenza vaccines, the World Health Organization stimulated the evaluation of different vaccination concepts including the use of live attenuated influenza vaccines (LAIVs). Therefore, we have immunized ferrets intranasally with a single dose of pH1N1-LAIV from different manufacturers. They all induced adequate serum HI antibody titers in the ferrets and protected them against intratracheal wild-type pH1N1 virus challenge: pH1N1 virus replication in the upper respiratory tract and lungs was reduced and no disease signs or severe broncho-interstitial pneumonia were observed in any of the vaccinated ferrets. These data together with the relatively efficient production process emphasize the potential of the LAIV concept for pandemic preparedness. © 2011 Elsevier Ltd.


De Stefano L.A.,Oklahoma State University | Stepanov I.I.,2 Academy Pavlov Street | Abramson C.I.,Oklahoma State University
Insects | Year: 2014

This paper describes a mathematical model of the learning process suitable for studies of conditioning using the proboscis extension reflex (PER) in honey bees when bees are exposed to agrochemicals. Although procedural variations exist in the way laboratories use the PER paradigm, proboscis conditioning is widely used to investigate the influence of pesticides and repellents on honey bee learning. Despite the availability of several mathematical models of the learning process, no attempts have been made to apply a mathematical model to the learning curve in honey bees exposed to agrochemicals. Our model is based on the standard transfer function in the form Y = B3 e-B2 (X-1) + B4 (1 - e-B2 (X-1)) where X is the trial number, Y is the proportion of correct responses, B2 is the learning rate, B3 is readiness to learn, and B4 is ability to learn. We reanalyze previously published data on the effect of several classes of agrochemicals including: (1) those that are considered harmless to bees (e.g., pymetrozine, essential oils, dicofol); (2) sublethal exposure to pesticides known to harm honey bees (e.g., coumaphos, cyfluthrin, fluvalinate, permethrin); and (3) putative repellents of honey bees (e.g., butyric acid, citronella). The model revealed additional effects not detected with standard statistical tests of significance. © 2014 by the authors; licensee MDPI, Basel, Switzerland.


Stepanov I.I.,2 Academy Pavlov Street | Abramson C.I.,Oklahoma State University | Warschausky S.,University of Michigan
Child Neuropsychology | Year: 2011

A mathematical model is proposed to measure the learning curve in the California Verbal Learning Test-Children's Version. The model is based on the first-order system transfer function in the form Y = B3*exp[-B2*(X- 1)]+B4*{1-exp[-B2*(X-1)]}, where X is the trial number, Y is the number of recalled correct words, B2 is the learning rate, B3 is interpreted as readiness to learn and B4 as the ability to learn. Children's readiness to learn and ability to learn were lower than adults. Modeling revealed that girls had greater readiness to learn and ability to learn than boys. © 2011 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business.


Abramson C.I.,Oklahoma State University | Stepanov I.I.,2 Academy Pavlov Street
Bulletin of Environmental Contamination and Toxicology | Year: 2012

No attempts have been made to apply a mathematical model to the learning curve in honey bees exposed to pesticides. We applied a standard transfer function in the form Y = B3*exp(-B2 *(X -1)) B4 *(1 -exp(-B2 *(X -1))), where X is the trial number; Y is proportion of correct responses, B2 is the learning rate, B3 is readiness to learn and B4 is ability to learn. Reanalyzing previously published data on the effect of insect growth regulators tebufenozide and diflubenzuron on the classical conditioning of proboscis extension, the model revealed additional effects not detected with standard statistical tests of significance. © Springer Science+Business Media, LLC 2012.


Stepanov I.I.,2 Academy Pavlov Street | Abramson C.I.,Oklahoma State University | Wolf O.T.,Ruhr University Bochum | Convit A.,New York University | Convit A.,Nathan Kline Institute for Psychiatric Research
Journal of the International Neuropsychological Society | Year: 2010

Very few attempts have been made to apply a mathematical model to the learning curve in the California Verbal Learning Test list A immediate recall. Our rationale was to find out whether modeling of the learning curve can add additional information to the standard CVLT-II measures. We applied a standard transfer function in the form Y = B3*exp(-B2*(X-1))+B4*(1- exp(-B2*(X-1))), where X is the trial number; Y is the number of recalled correct words, B2 is the learning rate, B3 is readiness to learn and B4 is ability to learn. The coefficients of the model were found to be independent measures not duplicating standard CVLT-II measures. Regression analysis revealed that readiness to learn (B3) and ability to learn (B4) were significantly (p <.05) higher in a group of healthy participants than in a group of participants with type 2 diabetes mellitus (T2DM), but the learning rate (B2) did not differ (p >.2). The proposed model is appropriate for clinical application and as a guide for research and may be used as a good supplemental tool for the CVLT-II and similar memory tests. Copyright © The International Neuropsychological Society 2010.

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