Interleukin-4 and interleukin-13 evoke scratching behaviour in mice

Persistent and relapsing itch commonly manifests in inflammatory skin disorders such as atopic dermatitis (AD). AD pathogenesis is driven by interleukin-4 (IL-4) and interleukin-13 (IL-13). Dupilumab, a monoclonal antibody blocking the action of IL-4 and IL-13 effectively reduces the symptoms of AD and itch. Little is known whether IL-4 and IL-13 directly contribute to itch transduction. A recently published study (Oetjen et al, Cell, 2017, 171, 217) found IL-4 and IL-13 to directly activate itch-sensory neurons in vitro. Surprisingly, they found no significant increase in scratching after intradermally injecting high doses (2.5 ug/ml) of IL-4 and IL-13 into mice. Similar experiments in our lab, however, suggested that both IL-4 and IL-13 contribute to acute itch in vivo. We intradermally injected lower doses (1 ug/ml) of IL-4 and IL-13 into mice and found a significant increase of scratching bouts compared to vehicle. Interestingly, the combined treatment of IL-4 and IL-13 produced additive increase of scratching and acute pruritus at an earlier time point compared to each cytokine administered alone. In summary, our study shows a rapid and significant increase of scratching after intradermal injection of IL-4, IL-13 or combined IL-4/ IL-13 compared to vehicle in mice 5-10 minutes after injection. Our data suggest that IL-4 and IL-13 alone and combined directly act as potent acute pruritogens on sensory nerves. This finding expands our understanding of cytokines as pruritogens, how targeted anticytokine medications act in AD, and about neuroimmune communication in the skin. - 2019 John Wiley & Sons A/S. Published by John Wiley & Sons LtdMs Michelle Campion performed the research, analysed the data and wrote the manuscript. Ms Leila Smith and Dr Solène Gatault aided in the research and analysed the data. Dr Charles Métais analysed the data. Dr Buddenkotte aided in the itch mouse model and wrote manuscript. Prof. Dr Dr Martin Steinhoff designed the research study, analysed the data and wrote manuscript. Study was funded by Science Foundation Ireland (IVP award to MS) and Qatar National Research Award (QNRF) (to MS). All authors have read and approved the final manuscript.Scopu

Protein expression profiling identifies key proteins and pathways involved in growth inhibitory effects exerted by guggulsterone in human colorectal cancer cells

Colorectal cancer (CRC) is a leading killer cancer worldwide and one of the most common malignancies with increasing incidences of mortality. Guggulsterone (GS) is a plant sterol used for treatment of various ailments such as obesity, hyperlipidemia, diabetes, and arthritis. In the current study, anti-cancer effects of GS in human colorectal cancer cell line HCT 116 was tested, potential targets identified using mass spectrometry-based label-free shotgun proteomics approach and key pathways validated by proteome profiler antibody arrays. Comprehensive proteomic profiling identified 14 proteins as significantly dysregulated. Proteins involved in cell proliferation/migration, tumorigenesis, cell growth, metabolism, and DNA replication were downregulated while the protein with functional role in exocytosis/tumor suppression was found to be upregulated. Our study evidenced that GS treatment altered expression of Bcl-2 mediated the mitochondrial release of cytochrome c which triggered the formation of apoptosome as well as activation of caspase-3/7 leading to death of HCT 116 cells via intrinsic apoptosis pathway. GS treatment also induced expression of p53 protein while p21 expression was unaltered with no cell cycle arrest. In addition, GS was found to inhibit NF-kB signaling in colon cancer cells by quelling the expression of its regulated gene products Bcl-2, cIAP-1, and survivin. - 2019 by the authors. Licensee MDPI, Basel, Switzerland.Funding: This study was funded by MEDICAL RESEARCH CENTER (MRC) at HAMAD MEDICAL CORPORATION, Doha, State of Qatar with grant number MRC#15264/15.Scopu

Understanding the Burden of Atopic Dermatitis in Africa and the Middle East

Atopic dermatitis (AD) is a common inflammatory skin disease characterized by intensely pruritic lesions. The prevalence of atopic dermatitis is increasing in developing regions, including Africa and the Middle East. However, these regions are underrepresented in the dermatology literature, and a better understanding of the growing burden of atopic dermatitis in Africa and the Middle East is necessary. Herein, we summarize current knowledge on atopic dermatitis epidemiology, disease burden, and treatment options in Africa and the Middle East, highlighting the unmet needs of patients in these regions. With these needs in mind, we provide clinical recommendations for appropriate management of atopic dermatitis in Africa and the Middle East. Funding: Pfizer Inc. Plain Language Summary: Plain language summary available for this article.Editorial/medical writing support under the guidance of the authors was provided by Madeline L. Pfau, PhD, and Corey Mandel, PhD, at ApotheCom, New York, NY, and San Francisco, CA, USA, and was funded by Pfizer Inc., New York, NY, USA, in accordance with Good Publication Practice (GPP3) guidelines ( Ann Intern Med. 2015;163:461-464).Scopu

Skin Barrier Homeostasis in Atopic Dermatitis: Feedback Regulation of Kallikrein Activity

Atopic dermatitis (AD) is a widely spread cutaneous chronic disease characterised by sensitive reactions (eg. eczema) to normally innocuous elements. Although relatively little is understood about its underlying mechanisms due to its complexity, skin barrier dysfunction has been recognised as a key factor in the development of AD. Skin barrier homeostasis requires tight control of the activity of proteases, called kallikreins (KLKs), whose activity is regulated by a complex network of protein interactions that remains poorly understood despite its pathological importance. Characteristic symptoms of AD include the outbreak of inflammation triggered by external (eg. mechanical and chemical) stimulus and the persistence and aggravation of inflammation even if the initial stimulus disappears. These characteristic symptoms, together with some experimental data, suggest the presence of positive feedback regulation for KLK activity by inflammatory signals. We developed simple mathematical models for the KLK activation system to study the effects of feedback loops and carried out bifurcation analysis to investigate the model behaviours corresponding to inflammation caused by external stimulus. The model analysis confirmed that the hypothesised core model mechanisms capture the essence of inflammation outbreak by a defective skin barrier. Our models predicted the outbreaks of inflammation at weaker stimulus and its longer persistence in AD patients compared to healthy control. We also proposed a novel quantitative indicator for inflammation level by applying principal component analysis to microarray data. The model analysis reproduced qualitative AD characteristics revealed by this indicator. Our results strongly implicate the presence and importance of feedback mechanisms in KLK activity regulation. We further proposed future experiments that may provide informative data to enhance the system-level understanding on the regulatory mechanisms of skin barrier in AD and healthy individuals

Role of mast cells and basophils in pruritus

To protect our body systems, there is a constant interactive conversation between the skin nervous and immune system. Important elements of this conversation in the skin include mast cells, basophils, and sensory nerve fibers. These cells employ a vast array of sensors that detect danger and react accordingly. This reaction, summarized as neurogenic inflammation, manifests at the conscious level as sensations including pain and itch. Here we provide a perspective on the blossoming knowledge that is illuminating connections between mast cells, basophils, and sensory nerve fibers in the mediation of itch. We discuss established mediators and receptors, in particular cytokine and neuropeptide pathways, upstream proteases, and proteinase-activated receptors, and the emerging role of mas-related G-protein-coupled receptors in itch. - 2018 John Wiley & Sons A/S. Published by John Wiley & Sons LtdHamad Medical Hospital Seed Funding, Doha, Qatar; NIH grants (from NIAMS), Grant/Award Number: R21AR067399 and R01AR057744; We thank Dr. Ayda Al-Hammadi for critically reading the manuscript. This study was supported by seed funding from Hamad Medical Corporation, Qatar (to M.S.).Scopu

Integrating Artificial Intelligence Tools in the Clinical Research Setting: The Ovarian Cancer Use Case.

Artificial intelligence (AI) methods applied to healthcare problems have shown enormous potential to alleviate the burden of health services worldwide and to improve the accuracy and reproducibility of predictions. In particular, developments in computer vision are creating a paradigm shift in the analysis of radiological images, where AI tools are already capable of automatically detecting and precisely delineating tumours. However, such tools are generally developed in technical departments that continue to be siloed from where the real benefit would be achieved with their usage. Significant effort still needs to be made to make these advancements available, first in academic clinical research and ultimately in the clinical setting. In this paper, we demonstrate a prototype pipeline based entirely on open-source software and free of cost to bridge this gap, simplifying the integration of tools and models developed within the AI community into the clinical research setting, ensuring an accessible platform with visualisation applications that allow end-users such as radiologists to view and interact with the outcome of these AI tools

Integrating Artificial Intelligence Tools in the Clinical Research Setting: The Ovarian Cancer Use Case

Peer reviewed: TrueArtificial intelligence (AI) methods applied to healthcare problems have shown enormous potential to alleviate the burden of health services worldwide and to improve the accuracy and reproducibility of predictions. In particular, developments in computer vision are creating a paradigm shift in the analysis of radiological images, where AI tools are already capable of automatically detecting and precisely delineating tumours. However, such tools are generally developed in technical departments that continue to be siloed from where the real benefit would be achieved with their usage. Significant effort still needs to be made to make these advancements available, first in academic clinical research and ultimately in the clinical setting. In this paper, we demonstrate a prototype pipeline based entirely on open-source software and free of cost to bridge this gap, simplifying the integration of tools and models developed within the AI community into the clinical research setting, ensuring an accessible platform with visualisation applications that allow end-users such as radiologists to view and interact with the outcome of these AI tools