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785 results on '"Rohani, Pejman"'

3. Human germline heterozygous gain-of-function STAT6 variants cause severe allergic disease

Author

Sharma, Mehul, Leung, Daniel, Momenilandi, Mana, Jones, Lauren CW, Pacillo, Lucia, James, Alyssa E, Murrell, Jill R, Delafontaine, Selket, Maimaris, Jesmeen, Vaseghi-Shanjani, Maryam, Del Bel, Kate L, Lu, Henry Y, Chua, Gilbert T, Di Cesare, Silvia, Fornes, Oriol, Liu, Zhongyi, Di Matteo, Gigliola, Fu, Maggie P, Amodio, Donato, San Tam, Issan Yee, Chan, Gavin Shueng Wai, Sharma, Ashish A, Dalmann, Joshua, van der Lee, Robin, Blanchard-Rohner, Géraldine, Lin, Susan, Philippot, Quentin, Richmond, Phillip A, Lee, Jessica J, Matthews, Allison, Seear, Michael, Turvey, Alexandra K, Philips, Rachael L, Brown-Whitehorn, Terri F, Gray, Christopher J, Izumi, Kosuke, Treat, James R, Wood, Kathleen H, Lack, Justin, Khleborodova, Asya, Niemela, Julie E, Yang, Xingtian, Liang, Rui, Kui, Lin, Wong, Christina Sze Man, Poon, Grace Wing Kit, Hoischen, Alexander, van der Made, Caspar I, Yang, Jing, Chan, Koon Wing, Da Rosa Duque, Jaime Sou, Lee, Pamela Pui Wah, Ho, Marco Hok Kung, Chung, Brian Hon Yin, Le, Huong Thi Minh, Yang, Wanling, Rohani, Pejman, Fouladvand, Ali, Rokni-Zadeh, Hassan, Changi-Ashtiani, Majid, Miryounesi, Mohammad, Puel, Anne, Shahrooei, Mohammad, Finocchi, Andrea, Rossi, Paolo, Rivalta, Beatrice, Cifaldi, Cristina, Novelli, Antonio, Passarelli, Chiara, Arasi, Stefania, Bullens, Dominique, Sauer, Kate, Claeys, Tania, Biggs, Catherine M, Morris, Emma C, Rosenzweig, Sergio D, O’Shea, John J, Wasserman, Wyeth W, Bedford, H Melanie, van Karnebeek, Clara DM, Palma, Paolo, Burns, Siobhan O, Meyts, Isabelle, Casanova, Jean-Laurent, Lyons, Jonathan J, Parvaneh, Nima, Van Nguyen, Anh Thi, Cancrini, Caterina, Heimall, Jennifer, Ahmed, Hanan, McKinnon, Margaret L, Lau, Yu Lung, Béziat, Vivien, and Turvey, Stuart E

Subjects
Genetics, Rare Diseases, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Inflammatory and immune system, Humans, STAT6 Transcription Factor, Gain of Function Mutation, Asthma, Food Hypersensitivity, Immunoglobulin E, Medical and Health Sciences, Immunology
Abstract

STAT6 (signal transducer and activator of transcription 6) is a transcription factor that plays a central role in the pathophysiology of allergic inflammation. We have identified 16 patients from 10 families spanning three continents with a profound phenotype of early-life onset allergic immune dysregulation, widespread treatment-resistant atopic dermatitis, hypereosinophilia with esosinophilic gastrointestinal disease, asthma, elevated serum IgE, IgE-mediated food allergies, and anaphylaxis. The cases were either sporadic (seven kindreds) or followed an autosomal dominant inheritance pattern (three kindreds). All patients carried monoallelic rare variants in STAT6 and functional studies established their gain-of-function (GOF) phenotype with sustained STAT6 phosphorylation, increased STAT6 target gene expression, and TH2 skewing. Precision treatment with the anti-IL-4Rα antibody, dupilumab, was highly effective improving both clinical manifestations and immunological biomarkers. This study identifies heterozygous GOF variants in STAT6 as a novel autosomal dominant allergic disorder. We anticipate that our discovery of multiple kindreds with germline STAT6 GOF variants will facilitate the recognition of more affected individuals and the full definition of this new primary atopic disorder.

Published
2023

10. Optimal non-pharmaceutical intervention policy for Covid-19 epidemic via neuroevolution algorithm

Author

Saeidpour, Arash and Rohani, Pejman

Subjects
Quantitative Biology - Populations and Evolution, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, 49N10, G.1.6
Abstract

National responses to the Covid-19 pandemic varied markedly across countries, from business-as-usual to complete shutdowns. Policies aimed at disrupting the viral transmission cycle and preventing the healthcare system from being overwhelmed, simultaneously exact an economic toll. We developed a intervention policy model that comprised the relative human, economic and healthcare costs of non-pharmaceutical epidemic intervention and arrived at the optimal strategy using the neuroevolution algorithm. The proposed model finds the minimum required reduction in contact rates to maintain the burden on the healthcare system below the maximum capacity. We find that such a policy renders a sharp increase in the control strength at the early stages of the epidemic, followed by a steady increase in the subsequent ten weeks as the epidemic approaches its peak, and finally control strength is gradually decreased as the population moves towards herd immunity. We have also shown how such a model can provide an efficient adaptive intervention policy at different stages of the epidemic without having access to the entire history of its progression in the population. This work emphasizes the importance of imposing intervention measures early and provides insights into adaptive intervention policies to minimize the economic impacts of the epidemic without putting an extra burden on the healthcare system., Comment: 18 pages, 10 figures

Published
2021

15. Nonlinear dynamic analysis of an epidemiological model for COVID-19 including public behavior and government action

Author

Kwuimy, C. A. K., Nazari, Foad, Jiao, Xun, Rohani, Pejman, and Nataraj, C.

Subjects
Quantitative Biology - Populations and Evolution, Physics - Physics and Society
Abstract

This paper is concerned with nonlinear modeling and analysis of the COVID-19 pandemic currently ravaging the planet. There are two objectives: to arrive at an appropriate model that captures the collected data faithfully, and to use that as a basis to explore the nonlinear behavior. We use a nonlinear SEIR (Susceptible, Exposed, Infectious & Removed) transmission model with added behavioral and government policy dynamics. We develop a genetic algorithm technique to identify key model parameters employing COVID19 data from South Korea. Stability, bifurcations and dynamic behavior are analyzed. Parametric analysis reveals conditions for sustained epidemic equilibria to occur. This work points to the value of nonlinear dynamic analysis in pandemic modeling and demonstrates the dramatic influence of social and government behavior on disease dynamics.

Published
2020
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23. Genomic Testing Identifies Monogenic Causes in Patients with Very Early-Onset Inflammatory Bowel Disease: A Multi-center Survey in an Iranian Cohort

Author

Eslamian, Golnaz, primary, Jamee, Mahnaz, additional, Momen, Tooba, additional, Rohani, Pejman, additional, Ebrahimi, Sarehossadat, additional, Mesdaghi, Mehrnaz, additional, Ghadimi, Soodeh, additional, Mansouri, Mahboubeh, additional, Mahdaviani, Seyed Alireza, additional, Sadeghi-shabestari, Mahnaz, additional, Fallahpour, Morteza, additional, Shamsian, Bibi Shahin, additional, Eslami, Narges, additional, Sharafian, Samin, additional, Dara, Naghi, additional, Nasri, Peiman, additional, Amini, Niloufar, additional, Enayat, Javad, additional, Fallahi, Mazdak, additional, Ghasemi Hashtrodi, Leila, additional, Shojaei, Mohammad, additional, Guevara Becerra, Martha, additional, Uhlig, Holm H, additional, and Chavoshzadeh, Zahra, additional

Published
2024
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34. Avoidable errors in the modeling of outbreaks of emerging pathogens, with special reference to Ebola

Author

King, Aaron A., de Cellès, Matthieu Domenech, Magpantay, Felicia M. G., and Rohani, Pejman

Subjects
Quantitative Biology - Populations and Evolution, Statistics - Applications
Abstract

As an emergent infectious disease outbreak unfolds, public health response is reliant on information on key epidemiological quantities, such as transmission potential and serial interval. Increasingly, transmission models fit to incidence data are used to estimate these parameters and guide policy. Some widely-used modeling practices lead to potentially large errors in parameter estimates and, consequently, errors in model-based forecasts. Even more worryingly, in such situations, confidence in parameter estimates and forecasts can itself be far over-estimated, leading to the potential for large errors that mask their own presence. Fortunately, straightforward and computationally inexpensive alternatives exist that avoid these problems. Here, we first use a simulation study to demonstrate potential pitfalls of the standard practice of fitting deterministic models to cumulative incidence data. Next, we demonstrate an alternative based on stochastic models fit to raw data from an early phase of 2014 West Africa Ebola Virus Disease outbreak. We show not only that bias is thereby reduced, but that uncertainty in estimates and forecasts is better quantified and that, critically, lack of model fit is more readily diagnosed. We conclude with a short list of principles to guide the modeling response to future infectious disease outbreaks., Comment: 40 pages, 11 figures, 2 tables. Published by Proceedings of the Royal Society of London, Series. Published online 1 April 2015

Published
2014
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35. Changes in lipid profile and glucose metabolism following administration of bupropion alone or in combination with naltrexone: A systematic review and meta‐regression analysis.

Author

Hu, Yi, Velu, Periyannan, Rohani, Pejman, and Sohouli, Mohammad Hassan

Subjects
GLUCOSE metabolism, BUPROPION, NALTREXONE, LIPID metabolism, LIPIDS
Abstract

Background: Considering the conflicting effects of bupropion on parameters related to metabolic syndrome including glucose metabolism and lipid profile, in this meta‐analysis study, we investigated the effects of this drug alone or in combination with naltrexone on glucose metabolism and lipid profile. Methods: Scopus, PubMed/Medline, Web of Science and Embase databases were searched using standard keywords to identify all controlled trials investigating effects of bupropion alone and combined with naltrexone on the glucose and lipid profile. Pooled weighted mean difference and 95% confidence intervals were achieved by random‐effects model. Results: Twelve studies with 5152 participants' were included in this article. The pooled findings showed that bupropion alone or in combination with naltrexone would significantly reduce glucose (weighted mean difference (WMD): −2.25 mg/dL, 95% confidence interval (CI): −4.10, −0.40), insulin (WMD: −4.06 μU/mL, 95% CI: −6.09, −2.03), homeostatic model assessment for insulin resistance (HOMA‐IR) (WMD: −0.58, 95% CI: −0.98, −0.19), triglyceride (TG) (WMD: −11.78 mg/dL, 95% CI: −14.48 to −9.08) and increase high‐density lipoprotein (HDL) (WMD: 2.68 mg/dL, 95% CI: 2.13 to 3.24). A Greater reduction in glucose levels was observed with duration >26 weeks. Dose of bupropion intake ≤360 mg and intervention for more than 26 weeks decreased insulin level significantly. With regard to lipid profile, reduction of triglycerides is more significant with dose of bupropion greater than 360 mg and a shorter intervention length equal to 26 weeks. Conclusions: The addition of combination therapies such as bupropion and naltrexone to lifestyle modification can significantly improve glucose metabolism and some lipid parameters. [ABSTRACT FROM AUTHOR]

Published
2024
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36. Managing the threat of infectious disease in fisheries and aquaculture using structured decision making.

Author

Irwin, Brian J, Tomamichel, Megan M, Frischer, Marc E, Hall, Richard J, Davis, Alaina DE, Bliss, Thomas H, Rohani, Pejman, and Byers, James E

Abstract

Fisheries and aquaculture provide food and economic security, especially in the developing world, but both face challenges from infectious disease. Here, we consider management of disease issues from a structured decision‐making perspective to examine how infectious disease can threaten seafood production and influence management decisions. For both wild fisheries and aquaculture, disease‐management objectives generally aim to mitigate the severity and economic burden of outbreaks. General management strategies include manipulating host densities, reducing system connectivity, conserving or improving habitat, and implementing direct treatments or some other biological interventions. To inform decisions, mathematical models can be used to explore disease dynamics and to forecast the potential effectiveness of alternative management actions. Developing and implementing disease‐management strategies also involve considering uncertainties and balancing competing stakeholder interests and risk tolerances. We conclude by outlining several steps for applying structured decision making that are broadly useful to decision makers facing issues related to disease. [ABSTRACT FROM AUTHOR]

Published
2024
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38. The epidemic volatility index, a novel early warning tool for identifying new waves in an epidemic

Author

Kostoulas, Polychronis, Meletis, Eletherios, Pateras, Konstantinos, Eusebi, Paolo, Kostoulas, Theodoros, Furuya-Kanamori, Luis, Speybroeck, Niko, Denwood, Matthew, Doi, Suhail A. R., Althaus, Christian L., Kirkeby, Carsten, Rohani, Pejman, Dhand, Navneet K., Peñalvo, José L., Thabane, Lehana, BenMiled, Slimane, Sharifi, Hamid, and Walter, Stephen D.

Published
2021
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42. The interaction of regional and local in the dynamics of the coffee rust disease

Author

Vandermeer, John and Rohani, Pejman

Subjects
Quantitative Biology - Populations and Evolution
Abstract

A simple mean field model is proposed that captures the two scales of dynamic processes involved in the spread of the coffee rust disease. At a local level the state variable is the fraction of coffee plants on an average farm that are infested with the disease and at the regional level the state variable is the fraction of farms that are infested with the disease. These two levels are interactive with one another in obvious ways, producing qualitatively interesting results. Specifically there are three distinct outcomes: disease disappears, disease is potentially persistent, and disease is inevitably persistent. The basic structure of the model generates the potential for tipping point behavior due to the presence of a blue sky bifurcation, suggesting that the emergence of epizootics of the disease may be unpredictable.

Published
2014

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