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Abdullah Ahmed , Ph.D.

Abdullah Ahmed

Dr. Abdullah Ahmed studierte an der Oxford Brookes University, wo er ein gemeinsames Promotionsprojekt zwischen der Universität und Evotec verfolgte, das sich auf die Charakterisierung des Mechanismus der Krebssignalgebung konzentrierte, um neue Ziele und Heilmittel zu finden. In der Central Laser Facility (CLF) in Harwell Oxford setzte er eine Vielzahl verschiedener Mikroskopsysteme ein, um seine Forschungen zum mTOR-Signalweg mit Hilfe von Bildgebung in fixierten und lebenden Zellen unter Verwendung fortschrittlicher Mikroskopie voranzutreiben. Er entwickelte und verwendete fluoreszierende Bildgebungstechnologien zur Beobachtung der Lokalisierung und Interaktionen von Proteinen in Verbindung mit FRET-FLIM (Förster-Resonanz-Energie-Transfer gemessen durch Fluoreszenz-Lebensdauer-Imaging-Mikroskopie). Nach Abschluss seines Studiums kam er 2019 als Advanced Workflow Specialist (4 Jahre) zu Leica Microsystems und ist seit 2023 im Global Business Excellence Team als Global Business Excellence Manager für Weitfeldmikroskopie tätig. 

Multiplexed Cell DIVE imaging to characterize the spatial landscape in Human Alzheimer’s Cortical Tissue

Probing Human Alzheimer's Cortical Section using Spatial Multiplexing

Alzheimer’s disease (AD) is the most common neurodegenerative disease and is characterized by the progressive decline of cognitive function. Spatial profiling of AD brain may reveal cellular…
AI-based transfection analysis (left) of U2OS cells which were transfected with a fluorescently labelled protein. A fluorescence image of the cells (right) is also shown. The analysis and imaging were performed with Mateo FL.

Leveraging AI for Efficient Analysis of Cell Transfection

This article explores the pivotal role of artificial intelligence (AI) in optimizing transfection efficiency measurements within the context of 2D cell culture studies. Precise and reliable…
AI-based cell counting performed with a phase-contrast and fluorescence image using the Mateo FL microscope.

Precision and Efficiency with AI-Enhanced Cell Counting

This article describes the use of artificial intelligence (AI) for precise and efficient cell counting. Accurate cell counting is important for research with 2D cell cultures, e.g., cellular dynamics,…
Image of confluent cells taken with phase contrast (left) and analyzed for confluency using AI (right).

AI Confluency Analysis for Enhanced Precision in 2D Cell Culture

This article explains how efficient, precise confluency assessment of 2D cell culture can be done with artificial intelligence (AI). Assessing confluency, the percentage of surface area covered,…
40x magnification of organoids cluster taken on Mateo TL.Cell type: esophageal squamous carcinoma; scale bar 15µm. Courtesy of bioGenous, China.

Overcoming Observational Challenges in Organoid 3D Cell Culture

Learn how to overcome challenges in observing organoid growth. Read this article and discover new solutions for real-time monitoring which do not disturb the 3D structure of the organoids over time.
3D-volume-rendered light-sheet microscope image of a spheroid showing depth coding in different colors.

Imaging of Anti-Cancer Drug Uptake in Spheroids using DLS

Spheroid 3D cell culture models mimic the physiology and functions of living tissues making them a useful tool to study tumor morphology and screen anti-cancer drugs. The drug AZD2014 is a recognized…
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