Biology subjects

Uhlig, S.

Publications and source records attributed to Uhlig, S..

3 recordsLinked to original sources

bioRxiv2021

Effects of Hydroxychloroquine and Azithromycin on iPSC-derived Cardiomyocytes: Considerations for the Treatment of COVID-19 Patients

Despite known adverse effects of hydroxychloroquine (HCQ) and azithromycin (AZM) on cardiac function, HCQ and AZM have been used as combination therapy in the treatment of COVID-19 patients. Recent clinical data indicate higher complication rates with HCQ/AZM combination treatment in comparison to monotherapy. Here, we used human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) to systematically investigate the effects of HCQ and AZM individually and in combination. The clinically observed QT prolongation caused by treatment with HCQ could be recapitulated in iPSC-CMs based on prolonged field potential duration (FPDc). Interestingly, HCQ-induced FPDc prolongation was strongly enhanced by combined treatment with AZM, although AZM alone slightly shortened FPDc in iPSC-CMs. Furthermore, combined treatment with AZM and HCQ leads to higher cardiotoxicity, more severe structural disarrangement, and more pronounced contractile and electrophysiological dysfunctions, compared to respective mono-treatments. First mechanistic insights underlying the synergistic effects of AZM and HCQ on iPSC-CM functionality are provided based on increased Cx43- and Nav1.5-protein levels. Taken together, our results highlight that combined treatment with HCQ and AZM strongly enhances the adverse effects on cardiomyocytes, providing mechanistic evidence for the high mortality in patients receiving HCQ/AZM combination treatment.

pharmacology and toxicology↗

bioRxiv2021

Validation of binary non-targeted approaches: mathematical framework and experimental designs

Non-targeted methods (NTMs) are being increasingly developed and adopted to detect food fraud and identify the authenticity of the food. Method validation is a critical step before bringing the NTMs to the routine to be assured of method performance and trust that its outcomes are reliable. However, the paucity of well structured and harmonized validation strategies has been one of the hurdles, withholding the exploitation of NTMs. This report aims to describe a validation framework for methods that involve binary classification, which are prevalent in non-targeted workflows. We foresee this work to contribute to filling the current gap in the provisions for NTM method validation; perhaps also push the dialogue further to collectively resolve existing challenges.

bioinformatics↗

bioRxiv2020

AI-based identification of grain cultivars via non-target mass spectrometry

Detection of food fraud and geographical traceability of ingredients is a continually sought goal for government institutions, producers, and consumers. Herein we explore the use of non-target high-resolution mass spectrometry approaches and demonstrate its utility through a particularly challenging case study - to distinguish wheat and spelt cultivars. By employing a data-independent acquisition (DIA) approach for sample measurement, the spectra are of considerable size and complexity. We utilize artificial intelligence (AI) algorithms (artificial neural networks) to evaluate the extensive proteomic footprint of several wheat and spelt cultivars. The AI model thus obtained is used to classify newer varieties of spelt, processed flour, and bread samples. Additionally, we discuss the validation of such a method coupling DIA and AI approaches. The novel framework for method validation enables calculation of precision parameters for facile comparison of the discriminatory power of the method and in the development of a reliable decision rule.

bioinformatics↗