Online Measurement System for Dynamic Flow Bioreactors to Study Barrier Integrity of hiPSC-Based Blood–Brain Barrier In Vitro Models

Choi, Jihyoung; Mathew, Sanjana; Oerter, Sabrina; Appelt‐Menzel, Antje; Hansmann, Jan; Schmitz, Tobias

doi:10.3390/bioengineering9010039

Cited by 8 publications

(3 citation statements)

References 61 publications

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“…Computational modeling and computer-aided drug design have contributed immensely to the successful development of drugs, especially in the contemporary pharmaceutical and drug industries. Integrating computer-aided drug design (CADD) into the development of GLUT has contributed to the enhancement of selective drug targeting with reduced toxicity and off-target effects [ 96 , 97 , 98 ]. However, few studies exist directly comparing the efficacy and safety of synthetic chemicals against natural substances for targeting glucose transferase (GLUT).…”

Section: Drugs That Target Glucose Metabolism Enzymesmentioning

confidence: 99%

Targeting Glucose Metabolism Enzymes in Cancer Treatment: Current and Emerging Strategies

Zhang

Huang

et al. 2022

Cancers

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Reprogramming of glucose metabolism provides sufficient energy and raw materials for the proliferation, metastasis, and immune escape of cancer cells, which is enabled by glucose metabolism-related enzymes that are abundantly expressed in a broad range of cancers. Therefore, targeting glucose metabolism enzymes has emerged as a promising strategy for anticancer drug development. Although several glucose metabolism modulators have been approved for cancer treatment in recent years, some limitations exist, such as a short half-life, poor solubility, and numerous adverse effects. With the rapid development of medicinal chemicals, more advanced and effective glucose metabolism enzyme-targeted anticancer drugs have been developed. Additionally, several studies have found that some natural products can suppress cancer progression by regulating glucose metabolism enzymes. In this review, we summarize the mechanisms underlying the reprogramming of glucose metabolism and present enzymes that could serve as therapeutic targets. In addition, we systematically review the existing drugs targeting glucose metabolism enzymes, including small-molecule modulators and natural products. Finally, the opportunities and challenges for glucose metabolism enzyme-targeted anticancer drugs are also discussed. In conclusion, combining glucose metabolism modulators with conventional anticancer drugs may be a promising cancer treatment strategy.

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Section: Drugs That Target Glucose Metabolism Enzymesmentioning

confidence: 99%

Targeting Glucose Metabolism Enzymes in Cancer Treatment: Current and Emerging Strategies

Zhang

Huang

et al. 2022

Cancers

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“…Bioreactor parts were made from poly(dimethylsiloxane) (PDMS) as previously published [26]. Briefly, the required structure was designed by CAD and 3D SLA-printed using the resin Model V2 (Formlabs, USA).…”

Section: Production Of Silicone-based Bioreactor Partsmentioning

confidence: 99%

Perfusable Tissue Bioprinted into a 3D-Printed Tailored Bioreactor System

Gensler,

Malkmus,

Ockermann

et al. 2024

Bioengineering

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Bioprinting provides a powerful tool for regenerative medicine, as it allows tissue construction with a patient’s specific geometry. However, tissue culture and maturation, commonly supported by dynamic bioreactors, are needed. We designed a workflow that creates an implant-specific bioreactor system, which is easily producible and customizable and supports cell cultivation and tissue maturation. First, a bioreactor was designed and different tissue geometries were simulated regarding shear stress and nutrient distribution to match cell culture requirements. These tissues were then directly bioprinted into the 3D-printed bioreactor. To prove the ability of cell maintenance, C2C12 cells in two bioinks were printed into the system and successfully cultured for two weeks. Next, human mesenchymal stem cells (hMSCs) were successfully differentiated toward an adipocyte lineage. As the last step of the presented strategy, we developed a prototype of an automated mobile docking station for the bioreactor. Overall, we present an open-source bioreactor system that is adaptable to a wound-specific geometry and allows cell culture and differentiation. This interdisciplinary roadmap is intended to close the gap between the lab and clinic and to integrate novel 3D-printing technologies for regenerative medicine.

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“…This facilitates the use of the presented method as an in-process control to monitor the development of cell-based therapeutic products. In the future, current limitations in sensitivity and maximum culture duration may be overcome by using microcoils for signal high-sensitivity signal detection and a (PDMS-based) bioreactor for continuous media supply for long-term culture of the appropriate cells and tissues [38]. In particular, cell viability must be interpreted in the context of the detection limit.…”

Section: Plos Computational Biologymentioning

confidence: 99%

Non-destructive classification of unlabeled cells: Combining an automated benchtop magnetic resonance scanner and artificial intelligence

et al. 2023

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In order to treat degenerative diseases, the importance of advanced therapy medicinal products has increased in recent years. The newly developed treatment strategies require a rethinking of the appropriate analytical methods. Current standards are missing the complete and sterile analysis of the product of interest to make the drug manufacturing effort worthwhile. They only consider partial areas of the sample or product while also irreversibly damaging the investigated specimen. Two-dimensional T1 / T2 MR relaxometry meets these requirements and is therefore a promising in-process control during the manufacturing and classification process of cell-based treatments. In this study a tabletop MR scanner was used to perform two-dimensional MR relaxometry. Throughput was increased by developing an automation platform based on a low-cost robotic arm, resulting in the acquisition of a large dataset of cell-based measurements. Two-dimensional inverse Laplace transformation was used for post-processing, followed by data classification performed with support vector machines (SVM) as well as optimized artificial neural networks (ANN). The trained networks were able to distinguish non-differentiated from differentiated MSCs with a prediction accuracy of 85%. To increase versatility, an ANN was trained on 354 independent, biological replicates distributed across ten different cell lines, resulting in a prediction accuracy of up to 98% depending on data composition. The present study provides a proof of principle for the application of T1 / T2 relaxometry as a non-destructive cell classification method. It does not require labeling of cells and can perform whole mount analysis of each sample. Since all measurements can be performed under sterile conditions, it can be used as an in-process control for cellular differentiation. This distinguishes it from other characterization techniques, as most are destructive or require some type of cell labeling. These advantages highlight the technique’s potential for preclinical screening of patient-specific cell-based transplants and drugs.

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Online Measurement System for Dynamic Flow Bioreactors to Study Barrier Integrity of hiPSC-Based Blood–Brain Barrier In Vitro Models

Cited by 8 publications

References 61 publications

Targeting Glucose Metabolism Enzymes in Cancer Treatment: Current and Emerging Strategies

Targeting Glucose Metabolism Enzymes in Cancer Treatment: Current and Emerging Strategies

Perfusable Tissue Bioprinted into a 3D-Printed Tailored Bioreactor System

Non-destructive classification of unlabeled cells: Combining an automated benchtop magnetic resonance scanner and artificial intelligence

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