AG Asif: Clinical Proteomics & Artificial Intelligence Group (CPAIG)

Functional endothelium is responsible for maintaining a balance between vasodilation and vasoconstriction, between inhibition and stimulation of cell proliferation and migration, and between thrombogenesis and fibrinolysis. The functional impairment of endothelium breaks this balance causing damage to the arterial wall. The CPAIG investigates the underlying mechanism of endothelial dysfunction (ED) and its contribution to the development of cardiovascular diseases. The CPAIG has long-standing expertise in the field of clinical proteomics and mass spectrometry for the quantitative and qualitative differential protein profiling, protein-protein interactions, DNA-Protein-interactions, drug protein targets and characterization of post-translational modifications. We utilize omics approaches to broaden our understanding of the mechanism behind the disease progression and investigating the new therapeutic options.

Inflammation, Tight-Junctions and Endothelial Dysfunction

Bromodomain Protein 4 (BRD4), binds multiple promoters as well as intergenic regions, particularly enhancer sequences. The BRD4 inhibition could block NF-kB-mediated super-enhancer formation to help treat inflammation and atherosclerosis. We seek to understand the role of BRD4 isoforms in endothelial dysfunction and how BRD4 inhibition could rescue the endothelium integrity during inflammation. Furthermore, using an endothelial cells (HUVECs) model, we investigate the influence of inflammation on endothelial monolayer tight junctions and the role played by the BRD4 inhibition in preserving its integrity.

Laminar- / Oscillating-Shear Stress and Endothelial Dysfunction

The level of fluid shear stress (FSS) acting on endothelial cells is higher in arterial vessels compared to venous vessels. The nature of FSS experienced by endothelial cells is a function of blood flow patterns generated by the cardiac cycle. We subject the human umbilical vein endothelial cells (HUVEC) to shear forces, as prevalent in vessels, using a special apparatus for both oscillatory and laminar shear stress to mimic a physiological situation. The cellular models are used to broaden our understanding of the influence of age and inflammation in the progression of atherosclerosis.

Clinical Artificial Intelligence

The demand for healthcare services is ever increasing in a world where average age and population is increasing. Many countries are experiencing chronic shortage of healthcare practitioners and medical assistant staff, and the situation has become even alarming with the ever-stretching COVID-19 Pandemic. Artificial intelligence (AI), empowered by the machine learning (ML) technology, is demonstrating its ability to assist the health care personnel to perform their duties and offer patients with more personalized medical care. However, currently only with very specific settings in clinical practices, medical researchers are benefiting from the application of AI. Hence, the real potential of AI in healthcare is yet to be explored.

We together with the Future Networks, eScience Group at the GWDG are working to develop AI solutions for the clinical settings to achieve the goal of personalized and precision medicine. A short overview of the ongoing projects in this regard is given below:

Artificial Intelligence Based Predictive Covid-19 Connecter – COVID-BOT (AI-NET-PROTECT)

COVID-19 pandemic has huge economical cost and poses dynamic medical, technical, psycho-sociological challenges. Large amount of data is being generated and made available on to the public domain in each aspect of the pandemic. It is already an enormous challenge to find the relevant information from data available on the public domains. Our aim is to identify the gaps and opportunities in the healthcare system and to transform it by employing AI and ML.

Artificial Intelligence Based Predictive Covid-19 Connecter is a sophisticated self-learning tool that crawls the web for SARS-CoV-2 and Covid-19 information. It harvests and sorts scientific, social and commercial information available on the public domain. It displays the harvested information in multidimensional way based on and in accordance with its relevance to the Covid-19/SARS-CoV-2.

https://www.celticnext.eu/project-ai-net-protect/#

Kontakt

Wissenschaftler

Prof. Dr. Abdul R. Asif

Prof. Dr. Abdul R. Asif

Kontaktinformationen

AG-Mitarbeiter

Dr. Amjad Zia

Dr. Amjad Zia

Kontaktinformationen

Koorperationspartner

AG-Mitarbeiter

Dr. Muzzamil Aziz

Dr. Muzzamil Aziz

Kontaktinformationen

  • Future Networks, eScience Group

AG-Mitarbeiter

Amirreza Fazely Hamedani

 Amirreza Fazely Hamedani

Kontaktinformationen

  • Future Networks, eScience Group

AG-Mitarbeiter

Sabih Ahmad Khan

 Sabih Ahmad Khan

Kontaktinformationen

  • Future Networks, eScience Group

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