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Pheno‐Morphological Screening and Acoustic Sorting of 3D Multicellular Aggregates Using Drop Millifluidics

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  • معلومة اضافية
    • Contributors:
      Centre de Recherche Paul Pascal (CRPP); Université de Bordeaux (UB)-Institut de Chimie - CNRS Chimie (INC-CNRS)-Centre National de la Recherche Scientifique (CNRS); Laboratoire Photonique, Numérique et Nanosciences (LP2N); Université de Bordeaux (UB)-Institut d'Optique Graduate School (IOGS)-Centre National de la Recherche Scientifique (CNRS); Treefrog Therapeutics; CNRS 80PrimeINCA PLBIO 20-135Fondation Simone et Cino Del DucaRegion Nouvelle AquitaineResearch Network of the University of Bordeaux Frontiers of Life; ANR-21-CE18-0038,REVIL,Systèmes cellulaires hépatiques tout-en-un basés sur des capsules creuses pour des tests de toxicité: une approche d'ingénierie pour une étude quantitative moléculaire et fonctionnelle(2021)
    • بيانات النشر:
      CCSD
      Wiley Open Access
    • الموضوع:
      2025
    • نبذة مختصرة :
      International audience ; Abstract Three‐dimensional multicellular aggregates (MCAs) like organoids and spheroids have become essential tools to study the biological mechanisms involved in the progression of diseases. In cancer research, they are now widely used as in vitro models for drug testing. However, their analysis still relies on tedious manual procedures, which hinders their routine use in large‐scale biological assays. Here, a novel drop millifluidic approach is introduced to screen and sort large populations containing over one thousand MCAs: ImOCAS (Image‐based Organoid Cytometry and Acoustic Sorting). This system utilizes real‐time image processing to detect pheno‐morphological traits in MCAs. They are then encapsulated in millimetric drops, actuated on‐demand using the acoustic radiation force. The performance of ImOCAS is demonstrated by sorting spheroids with uniform sizes from a heterogeneous population, and by isolating organoids from spheroids with different phenotypes. This approach lays the groundwork for high‐throughput screening and high‐content analysis of MCAs with controlled morphological and phenotypical properties, which promises accelerated progress in biomedical research.
    • الرقم المعرف:
      10.1002/advs.202410677
    • الدخول الالكتروني :
      https://hal.science/hal-04891509
      https://hal.science/hal-04891509v1/document
      https://hal.science/hal-04891509v1/file/Advanced%20Science%20-%202025%20-%20Rembotte%20-%20Pheno%E2%80%90Morphological%20Screening%20and%20Acoustic%20Sorting%20of%203D%20Multicellular%20Aggregates.pdf
      https://doi.org/10.1002/advs.202410677
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.2E2619D2