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Phthalates are a class of endocrine-disrupting chemicals that have been shown to negatively correlate with thyroid hormone serum levels in humans and to cause a state of hyperactivity in the thyroid. However, their mechanism of action is not well described at the molecular level., SCOPUS: ar.j, info:eu-repo/semantics/published

Thyroid is a glandular tissue in the human body in which the function can be severely affected by endocrine disrupting chemicals (EDCs). Current in vitro assays to test endocrine disruption by chemical compounds are largely based on 2D thyroid cell cultures, which often fail to precisely evaluate the safety of these compounds. New and more advanced 3D cell culture systems are urgently needed to better recapitulate the thyroid follicular architecture and functions and help to improve the predictive power of such assays. Herein, the development of a thyroid organoid-on-a-chip (OoC) device using polymeric membranous carriers is described. Mouse embryonic stem cell derived thyroid follicles are incorporated in a microfluidic chip for a 4 day experiment at a flow rate of 12 µL min−1. A reversible seal provides a leak-tight sealing while enabling quick and easy loading/unloading of thyroid follicles. The OoC model shows a high degree of functionality, where organoids retain expression of key thyroid genes and a typical follicular structure. Finally, transcriptional changes following benzo[k]fluoranthene exposure in the OoC device demonstrate activation of the xenobiotic aryl hydrocarbon receptor pathway. Altogether, this OoC system is a physiologically relevant thyroid model, which will represent a valuable tool to test potential EDCs., SCOPUS: ar.j, info:eu-repo/semantics/published

The analysis of the combined mRNA and miRNA content of a biological sample can be of interest for answering several research questions, like biomarkers discovery, or mRNA–miRNA interactions. However, the process is costly and time-consuming, separate libraries need to be prepared and sequenced on different flowcells. Combo-Seq is a library prep kit that allows us to prepare combined mRNA–miRNA libraries starting from very low total RNA. To date, no dedicated bioinformatics method exists for the processing of Combo-Seq data. In this paper, we describe CODA (Combo-seq Data Analysis), a workflow specifically developed for the processing of Combo-Seq data that employs existing free-to-use tools. We compare CODA with exceRpt, the pipeline suggested by the kit manufacturer for this purpose. We also evaluate how Combo-Seq libraries analysed with CODA perform compared with conventional poly(A) and small RNA libraries prepared from the same samples. We show that using CODA more successfully trimmed reads are recovered compared with exceRpt, and the difference is more dramatic with short sequencing reads. We demonstrate how Combo-Seq identifies as many genes and fewer miRNAs compared to the standard libraries, and how miRNA validation favours conventional small RNA libraries over Combo-Seq. The CODA code is available at https://github.com/marta-nazzari/CODA., info:eu-repo/semantics/published