Bioprocess optimization for generation of hepatocytes derived from hiPSC and its application in primary hyperoxaluria type 1 disease modelling

Primary hyperoxaluria type 1 (PH1) is a rare metabolic disorder caused by mutations in the hepatic alanine-glyoxylate aminotransferase (AGT). Defective AGT in PH1 patients is characterized by excessive oxalate synthesis, which leads to a broad range of kidney complications including the end-stage renal disease [1]. Combined liver-kidney transplantation remains the only effective treatment; however significant morbidity, mortality and costs encouraged the development of advanced cell- and gene-based therapies for PH1. Thus, our aim was to implement a novel strategy to generate high numbers of functional hepatocyte-like cells (HLC) from PH1 patient derived human induced pluripotent stem cells (PH1.hiPSC), for PH1 disease modelling and further application in drug and therapeutics development. PH1.HLC were differentiated as 3D aggregates in stirred-tank bioreactors (STB) operated in perfusion, according to the integrated bioprocess previously developed by our group [2,3]. Briefly, PH1.hiPSC were aggregated and expanded in STB for 4 days preceding the hepatic differentiation. hiPSC to HLC commitment begin by culturing the 3D aggregates in different medium formulations (from Takara BioEurope AB). Two different dissolved oxygen (pO2) conditions were explored: a normoxia (pO2: uncontrolled, 95% air, 5% CO2) throughout the differentiation process (21 days) and a hypoxia with a low oxygen (pO2: 4% O2) environment between day 4 and day 14 of the differentiation. Our results showed that PH1-hiPSC successfully proliferated as 3D aggregates with an expansion factor of 6-fold after 4 days in culture while maintaining their pluripotent phenotype. Low dissolved oxygen concentration during hepatic specification, generate higher yields of HLC and improve gene expression levels of ALB, A1AT and CYP3A4 hepatic markers when compared with HLC differentiated under uncontrolled pO2 conditions. Moreover, Flow cytometry analysis, revealed a higher hepatocyte content of 80% (low pO2) vs 43% (uncontrolled pO2) for albumin, showing a higher process efficiency. Transcriptomic analysis using RNAseq confirmed that hepatocyte differentiation was enhanced in the low dissolved oxygen condition. In addition, these PH1.HLC showed functional characteristics typical of hepatocytes including production of important hepatic proteins (albumin, alpha 1 antitrypsin), urea and bile acids. PH1.HLC also display drug metabolization capacity, CYP450 activity and, by histological assessment, glycogen storage and positive staining for albumin and AFP markers. To further characterize the PH1 disease features, we performed a detailed metabolomic analysis and demonstrated that PH1.HLC show defective AGT activity with significantly higher production and secretion of oxalate for PH1.HLC when compared with HLC generated from healthy counterparts. Overall, controlling the dissolved oxygen concentration at key stages of the hepatic differentiation process improved cell yield and the maturation status of HLC. The bioprocess developed and optimized in this work offers high relevance not only for generation of more accurate in vitro models to study PH1 rare disease, but also towards the development of novel therapies. Acknowledgements & Funding: this study was funded by a grant from ERA-NET E-Rare 3 research program, JTC ERAdicatPH (E-Rare3/0002/2015) and Fundação para a Ciência e Tecnologia project MetaCardio (PTDC/BTM-SAL/32566/2017); iNOVA4Health – UIDB/04462/2020 and UIDP/04462/2020, a program financially supported by Fundação para a Ciência e Tecnologia/Ministério da Ciência, Tecnologia e Ensino Superior, through national funds is acknowledged. P. V., J. I. A. were supported by FCT fellowships SFRH/BD/145767/2019, SFRH/BD/116780/2016 respectively. [1] P. Cochat, N. Engl. J. Med., vol. 369, no. 7, pp. 649–658, 2013. [2] B. Abecasis, J. Biotechnol., vol. 246, pp. 81–93, 2017. [3] I. Isidro, Biotechnol Bioeng, vol. 118, 3610–3617, 2021

Advancing manufacture of hiPSC-derived hepatocytes with improved functionality: A nature-inspired protocol

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Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

A four-country cross-case analysis of academic staff expectations about learning analytics in higher education

The purpose of this paper is to explore the expectations of academic staff to learning analytics services from an ideal as well as a realistic perspective. This mixed-method study focused on a cross-case analysis of staff from Higher Education Institutions from four European universities (Spain, Estonia, Netherlands, UK). While there are some differences between the countries as well as between ideal and predicted expectations, the overarching results indicate that academic staff sees learning analytics as a tool to understand the learning activities and possibility to provide feedback for the students and adapt the curriculum to meet learners' needs. However, one of the findings from the study across cases is the generally consistently low expectation and desire for academic staff to be obligated to act based on data that shows students being at risk of failing or under-performing.</p

A four-country cross-case analysis of academic staff expectations about learning analytics in higher education

The purpose of this paper is to explore the expectations of academic staff to learning analytics services from an ideal as well as a realistic perspective. This mixed-method study focused on a cross-case analysis of staff from Higher Education Institutions from four European universities (Spain, Estonia, Netherlands, UK). While there are some differences between the countries as well as between ideal and predicted expectations, the overarching results indicate that academic staff sees learning analytics as a tool to understand the learning activities and possibility to provide feedback for the students and adapt the curriculum to meet learners' needs. However, one of the findings from the study across cases is the generally consistently low expectation and desire for academic staff to be obligated to act based on data that shows students being at risk of failing or under-performing.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Web Information System

A four-country cross-case analysis of academic staff expectations about learning analytics in higher education

The purpose of this paper is to explore the expectations of academic staff to learning analytics services from an ideal as well as a realistic perspective. This mixed-method study focused on a cross-case analysis of staff from Higher Education Institutions from four European universities (Spain, Estonia, Netherlands, UK). While there are some differences between the countries as well as between ideal and predicted expectations, the overarching results indicate that academic staff sees learning analytics as a tool to understand the learning activities and possibility to provide feedback for the students and adapt the curriculum to meet learners&#39; needs. However, one of the findings from the study across cases is the generally consistently low expectation and desire for academic staff to be obligated to act based on data that shows students being at risk of failing or under-performing.The data underlying this manuscript was collected in the SHEILA project co-funded by the Erasmus+ Programme of the European Union