Hypoxia-on-chip : from technological developments to biological applications
Notice bibliographique
Résumé
In vivo tumor cells experience low oxygen levels (15mmHg ( for lung cancer), called“hypoxia”, as compared to “physioxia” seen in healthy tissue (40mmHg ( for lung). Thishypoxic environment is mainly due to the fast proliferation rate of tumor cells along with the creation of abnormal vasculature. Hypoxia promotes malignant progression and reduces drug efficiency. Tumor on chip are promising models to reca pitulate in vitro the 3D architecture and the physiology of human solid tumor, such as cell cell and cell matrix interactions as well as biochemical gradients of drugs and nutrients. It is not yet possible to experimentally reproduce in vitro physio pathological hypoxia because the most adopted technology hypoxic incubator come with two major drawbacks: the lack of measurement of the oxygen level in the medium and the long equilibratio n time . At the beginning of my thesis , there we re no commercial systems capable to reproduce gradients of oxygen and pH inside microfluidic systems, mimicking not only global hypoxia, but also the fluctuations of local oxygen concentration due to angiogene sis and vessel leakages. I developed OXALIS (Oxygen ALImentation System), a new system to control the dissolved oxygen level in cell culture medium while perfusing a microfluidic chip withunprecedented performance in terms of response time (200sec), accur acy (2mmHg) and liquid flow control accuracy (0.1µL/min) min).To ensure proper oxygen control, microfluidic chips must be made of materials with lowoxygen permeability. Thermoplastics like cyclic olefin copolymer possess permeabilityapproximately 1,000 tim es lower than polydimethylsiloxane but retain oxygen due to their high oxygen solubility. Therefore, glass is the best material for hermetic chips, but its production necessitates clean rooms and specialized equipment. I worked on a cost effective chip fabrication procedure that eliminates the need for clean rooms, involving the assembly of glass slides using an adhesive layer. A comparative analysis of different adhesives was conducted to determine the adhesive with optimal properties for oxygen control, m inimizing the response time required to reach the desired oxygen levels and ensuring long term maintenance of the target oxygen concentrations. These findings demonstrate the feasibility of constructing a microfluidic chip that achieves optimal oxygen cont rol performance similar to that of glass .I then applied these technological developments to the biological question of hypoxiainduced drug resistance. I first demonstrated the capacity of OXALIS to recapitulate on chip the oxygen dependent transcriptomic modulations : the expression of the CA9 gene, a well established hypoxia inducible factors (HIF) target robustly increased after 1h of perfusion with OXALIS at 15mmHg (2 % O 2 )). Hypoxia can lead to various alterations in cell b ehaviour, including abnormal fusion of mitochondria, which may contribute to drug resistance. Despite the significance of these mitochondrial changes, comprehensive studies on real time mitochondrial phenotypes, particularly at the cellular population leve l, are lacking. This limitation is primarily due to the technical difficulties in combining live imaging and oxygen control in cell culture. Using two populations of A549 lung cancer cells, one resistant and one sensitive to paclitaxel, we performed continuous monitoring of mitochondrial shape under tightly controlled hypoxic conditions.By developing an innovative oxygen controller for tumoron chip models, I have successfully overcome technological barriers related to precision and response time. I exp lored novel biological inquiries, such as the evolution of mitochondrial morphology over time in response to varying oxygen concentrations and its correlation with resistance to anti cancer treatments.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».