DEVICE FOR AND USE OF THE DEVICE IN CULTIVATING TISSUE AND OBSERVING  CONTRACTIONS OF THE TISSUE

    公开(公告)号:EP4403621A1

    公开(公告)日:2024-07-24

    申请号:EP23152532.0

    申请日:2023-01-19

    摘要: A device (1) for cultivating tissue (28) and observing contractions of the tissue (28) comprises a lower component (2), the lower component (2) defining a culture chamber (5) having a transparent bottom, a side wall and an open top, and an upper component (6) fitting on the lower component (2) and having a base plate (7) and two elastic posts (9). Each of the two elastic posts (9) extends downwards from the base plate (7) and has an upper post end (11) that is fixed to the base plate (7) and a free lower post end (10). The two elastic posts (9) are arranged at a lateral post distance (16). When the upper component (6) is fitted on the lower component (2), the two elastic posts (9) extend into the culture chamber (5), the two elastic posts (9) being arranged at lateral wall distances to the sidewall and their lower post ends (10) facing the bottom of the culture chamber (5). Each of the two elastic posts (9) includes a light guide (12) configured and arranged for coupling-in light (29) at the respective upper post end (11) and for coupling-out the light (29) at the respective lower post end (10) and through the bottom of the culture chamber (5). A piezoelectric bending transducer (13) extends downwards from the base plate (7) and has an upper transducer end (14) that is fixed to the base plate (7) and a lower transducer end (15) that is attached to one of the two elastic posts (9) at a vertical distance to its lower post end (10).

    METHOD AND APPARATUS FOR TRAINING A COMPUTER-IMPLEMENTED MACHINE-LEARNING MODEL

    公开(公告)号:EP4372617A1

    公开(公告)日:2024-05-22

    申请号:EP23169568.5

    申请日:2023-04-24

    摘要: A method for training a computer-implemented machine-learning model f for controlling a system by control parameter y, wherein said model has been trained to predict a target variable y = f(x) based on an input feature value X, where X is an input value feature value obtained by one or more sensors and used to generate by said model said target variable y as control parameter to thereby control said system,
    wherein said model f has been trained using a first set of training data (yk, xk) corresponding to k =1... N time points to find the trained machine learning model f*
    wherein a backward model g* has been trained based on at least a part of said first set of training data (yk, xk) to predict an input feature value xk+1 based on its preceding input feature value xk and the corresponding target variable yk, said method comprising:
    using said backward model g* to generate second set of training data, which comprises the future input feature values xk+1 predicted by the backward machine learning model g* and the corresponding ground truth variable yk+1,
    training said model f, which has been trained using said first set of training data, using said replay buffer as said second set of training data.

    AI-ASSISTED GENERATION OF ANNOTATED MEDICAL IMAGES

    公开(公告)号:EP4239589A1

    公开(公告)日:2023-09-06

    申请号:EP22159493.0

    申请日:2022-03-01

    摘要: A method for AI-assisted generation of annotated medical images (WSI) is described. In the method, a set (S) of pre-annotated medical images (WSI) is received. Then the received set (S) is processed by automatically performing the steps of training an AI-based uncertainty model (BSM) using the received set (S) as training data. Then, a step of processing medical images (WSI) of the received set (S) by determining classified segments (SG) and/or uncertainty regions (UR) in the medical images (WSI) using the trained AI-based uncertainty model (BSM) follows. Further, a step of selecting at least a part of the processed medical images (WSI) including classified segments and/or uncertainty regions (UR) based on the processing result and presenting the selected part of processed medical images (WSI) to a human expert (HE) is performed. Furthermore, a modified received set (S') including additional annotations (AA) created by the human expert (HE) is received. The mentioned steps can be repeated using the modified set (S') of medical images (WSI) as training data, until a predetermined quality criteria for the annotated medical images (WSI) is achieved. Further, an annotation assistance device (10) is described. Furthermore, a computer-implemented method for providing a segmented medical image is described.

    MASS PRODUCTION OF HUMAN PLURIPOTENT STEM CELL DERIVED CARDIAC STROMAL CELL

    公开(公告)号:EP3945133A8

    公开(公告)日:2023-04-12

    申请号:EP20188364.2

    申请日:2020-07-29

    IPC分类号: C12N5/077 C12N5/071

    摘要: The application describes a method for producing a population of cardiac stromal cells from pluripotent stem cells. Specifically, the method relates to (i) inducing epithelial-mesenchymal transition of pluripotent stem cell derived epicardial cells and (ii) amplifying the number of cardiac stromal cells in serum-free conditions. These cardiac stromal cells can be mass produced according to the described method and said cells maintain the expression of CD90, CD73 and CD44 in at least 80% of the cardiac stromal cells. Furthermore, the application relates to a population of cardiac stromal cells, which are pluripotent stem cells derived and wherein at least 80% of the cardiac stromal cells express CD90, CD73 and CD44. Said cardiac stromal form the basis for several in vitro and in vivo applications such as the production of engineered organ tissue and the support of, for example, heart repair. Also, a serum-free culture medium for the amplification of cardiac stromal cells is provided herein.