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An optimized derivative of an endogenous CXCR4 antagonist prevents atopic dermatitis and airway inflammation

Acta Pharmaceutica Sinica B 2021年第9期11卷 2694-2708页

作者： Mirja Harms Monica MWHabib Simona Nemska Antonella Nicolò Andrea Gilg Nico Preising Pandian Sokkar Sara Carmignani Martina Raasholm Gilbert Weidinger Gönül Kizilsavas Manfred Wagner Ludger Ständker ashraf habadi Hassan Jumaa Frank Kirchhoff Nelly Frossard Elsa Sanchez-Garcia Jan Münch Institute of Molecular Virology Ulm University Medical CenterUlm 89081Germany Department of Pharmaceutical Chemistry Faculty of Pharmacy and BiotechnologyGerman University in CairoCairo 11835Egypt Laboratoire D'Innovation Thérapeutique UMR7200 CNRS/Universitéde Strasbourg and LabEx MEDALISFacultéde PharmacieIllkirch 67412France Institute of Immunology Ulm University Medical CenterUlm 89081Germany Core Facility Functional Peptidomics Ulm University Medical CenterUlm 89081Germany Center of Medical Biotechnology University of Duisburg-EssenDuisburg 47057Germany Max-Planck-Institute for Coal Research Düsseldorf 45470Germany Faculty of Allied Health Sciences Chettinad Hospital and Research InstituteChettinad Academy of Research and EducationKelambakkam 603103India Max-Planck-Institut für Molekulare Physiologie Dortmund 44227Germany Institute of Biochemistry and Molecular Biology Ulm UniversityUlm 89081Germany Max Planck Institute for Polymer Research Mainz 55128Germany

Aberrant CXCR4/CXCL12 signaling is involved in many pathophysiological processes such as cancer and inflammatory diseases.A natural fragment of serum albumin,named EPI-X4,has previously been identified as endogenous peptide antagonist and inverse agonist of CXCR4 and is a promising compound for the development of improved analogues for the therapy of CXCR4-associated *** generate optimized EPI-X4 derivatives we here performed molecular docking analysis to identify key interaction motifs of EPI-X4/*** rational drug design allowed to increase the anti-CXCR4 activity of *** EPI-X4 derivative JM#21 bound CXCR4 and suppressed CXCR4-tropic HIV-1 infection more efficiently than the clinically approved small molecule CXCR4 antagonist ***-X4 JM#21 did not exert toxic effects in zebrafish embryos and suppressed allergen-induced infiltration of eosinophils and other immune cells into the airways of animals in an asthma mouse ***,topical administration of the optimized EPI-X4 derivative efficiently prevented inflammation of the skin in a mouse model of atopic ***,rationally designed EPIX4 JM#21 is a novel potent antagonist of CXCR4 and the first CXCR4 inhibitor with therapeutic efficacy in atopic *** clinical development of this new class of CXCR4 antagonists for the therapy of atopic dermatitis,asthma and other CXCR4-associated diseases is highly warranted.

关键词： CXCR4 antagonist Asthma Allergy Inflammation Atopic dermatitis

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Alzheimer’s Disease: The Relative Importance Diagnostic

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Advances in Alzheimer's Disease 2020年第4期9卷 77-86页

作者： Maryam habadi Christos P. Tsokos Departmentof Statistics King Abdulaziz University Jeddah KSA Department of Mathematics and Statistics University of South Florida Tampa USA

As the population ages, Alzheimer’s disease is rapidly increasing, and the diagnosis of the disease is still poorly understood. In comparison to cancer, 90% of patients become aware of their diagnosis, but only 45% of the people with Alzheimer’s are aware. Thus, the need for biomarkers for reliable diagnosis is tremendous to help in finding treatment for this serious disease. Hence, the main aim of this paper is to utilize information from baseline measurements to develop a statistical prediction model using multiple logistic regression to distinguish Alzheimer’s disease patients from cognitively normal individuals. Our optimal predictive model includes six risk factors and two interaction terms and has been evaluated using classification accuracy, sensitivity, specificity values and area under the curve.

关键词： Alzheimer’s Disease Multiple Logistic Regression Predictive Model Classification Accuracy

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Statistical Forecasting Models of Atmospheric Carbon Dioxide and Temperature in the Middle East

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Journal of Geoscience and Environment Protection 2017年第10期5卷 11-21页

作者： Maryam I. habadi Chris P. Tsokos Department of Mathematics and Statistics University of South Florida Tampa USA

Time series models are very powerful methods that help to drive hidden visions of a phenomenon and make informed future decisions. The purpose of this study is to develop statistical time series forecasting models to predict atmospheric carbon dioxide concentration in the Middle East and temperature in Saudi Arabia using multiplicative seasonal autoregressive integrated moving average models. We proceed to verify the quality and usefulness of our proposed probabilistic models by utilizing essential statistical properties to evaluate them according to their performance in forecasting the carbon dioxide in the atmosphere and the corresponding temperatures and it was shown that both statistical forecasting models produced good estimates.

关键词： Non-Stationary Time Series ARIMA Global Warming

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