""" .. _SectionExampleSingleCell: Classic TFM (liver fibroblasts) =============================== This example evaluates three hepatic stellate cells in 1.2mg/ml collagen with relaxed and deformed stacks. The relaxed stacks were recorded with cytochalasin D treatment of the cells. This example can also be evaluated with the graphical user interface. .. figure:: ../images/examples/single_cell_tfm/liver_fibroblasts.png """ import saenopy # sphinx_gallery_thumbnail_path = '../../saenopy/img/thumbnails/liver_fibroblast_icon.png' # %% # Downloading the example data files # ---------------------------------- # The folder structure is as follows. There are three cells recorded at different positions in the gel (Pos004, Pos007, Pos008) and three # channels (ch00, ch01, ch02). The stack has 376 z positions (z000-z375). All positions are recorded once in the active # state ("Deformed") and once after relaxation with Cyto D as the reference state ("Relaxed"). # # :: # # 1_ClassicSingleCellTFM # ├── Deformed # │ └── Mark_and_Find_001 # │ ├── Pos004_S001_z000_ch00.tif # │ ├── Pos004_S001_z000_ch01.tif # │ ├── Pos004_S001_z000_ch02.tif # │ ├── Pos004_S001_z001_ch02.tif # │ ├── ... # │ ├── Pos007_S001_z001_ch00.tif # │ ├── ... # │ ├── Pos008_S001_z001_ch02.tif # │ └── ... # └── Relaxed # └── Mark_and_Find_001 # ├── Pos004_S001_z000_ch00.tif # ├── Pos004_S001_z000_ch01.tif # ├── Pos004_S001_z000_ch02.tif # ├── Pos004_S001_z001_ch02.tif # ├── ... # ├── Pos007_S001_z001_ch00.tif # ├── ... # ├── Pos008_S001_z001_ch02.tif # └── ... # # download the data saenopy.load_example("ClassicSingleCellTFM") # %% # Loading the Stacks # ------------------ # # Saenopy is very flexible in loading stacks from any filename structure. # Here we replace the number in the position "Pos004" with an asterisk "Pos*" to batch process all positions. # We replace the number of the channels "ch00" with a channel placeholder "ch{c:00}" to indicate that this refers to # the channels and which channel to use as the first channel where the deformations should be detected. # We replace the number of the z slice "z000" with a z placeholder "z{z}" to indicate that this number refers to the # z slice. We do the same for the deformed state and for the reference stack. # load the relaxed and the contracted stack # {z} is the placeholder for the z stack # {c} is the placeholder for the channels # {t} is the placeholder for the time points results = saenopy.get_stacks( '1_ClassicSingleCellTFM/Deformed/Mark_and_Find_001/Pos*_S001_z{z}_ch{c:00}.tif', reference_stack='1_ClassicSingleCellTFM/Relaxed/Mark_and_Find_001/Pos*_S001_z{z}_ch{c:00}.tif', output_path='1_ClassicSingleCellTFM/example_output', voxel_size=[0.7211, 0.7211, 0.988]) # %% # Detecting the Deformations # -------------------------- # Saenopy uses 3D Particle Image Velocimetry (PIV) with the following parameters # to calculate matrix deformations between a deformed and relaxed state # for three example cells. # # +------------------+-------+ # | Piv Parameter | Value | # +==================+=======+ # | element_size | 14 | # +------------------+-------+ # | window_size | 35 | # +------------------+-------+ # | signal_to_noise | 1.3 | # +------------------+-------+ # | drift_correction | True | # +------------------+-------+ # # define the parameters for the piv deformation detection piv_parameters = {'element_size': 14.0, 'window_size': 35.0, 'signal_to_noise': 1.3, 'drift_correction': True} # iterate over all the results objects for result in results: # set the parameters result.piv_parameters = piv_parameters # get count count = len(result.stacks) if result.stack_reference is None: count -= 1 # iterate over all stack pairs for i in range(count): # get two consecutive stacks if result.stack_reference is None: stack1, stack2 = result.stacks[i], result.stacks[i + 1] # or reference stack and one from the list else: stack1, stack2 = result.stack_reference, result.stacks[i] # and calculate the displacement between them result.mesh_piv[i] = saenopy.get_displacements_from_stacks(stack1, stack2, piv_parameters["window_size"], piv_parameters["element_size"], piv_parameters["signal_to_noise"], piv_parameters["drift_correction"]) # save the displacements result.save() # %% # Generating the Finite Element Mesh # ---------------------------------- # Interpolate the found deformations onto a new mesh which will be used for the regularisation. We use identical element # size of deformation detection mesh here and keep the overall mesh size the same. # # +------------------+-------+ # | Mesh Parameter | Value | # +==================+=======+ # | element_size | 14 | # +------------------+-------+ # | mesh_size | 'piv' | # +------------------+-------+ # | reference_stack |'first'| # +------------------+-------+ # # define the parameters to generate the solver mesh and interpolate the piv mesh onto it mesh_parameters = {'reference_stack': 'first', 'element_size': 14.0, 'mesh_size': 'piv'} # iterate over all the results objects for result in results: # correct for the reference state displacement_list = saenopy.subtract_reference_state(result.mesh_piv, mesh_parameters["reference_stack"]) # set the parameters result.mesh_parameters = mesh_parameters # iterate over all stack pairs for i in range(len(result.mesh_piv)): # and create the interpolated solver mesh result.solvers[i] = saenopy.interpolate_mesh(result.mesh_piv[i], displacement_list[i], mesh_parameters) # save the meshes result.save() # %% # Calculating the Forces # ---------------------- # Define the material model and run the regularisation to fit the measured deformations and get the forces. # # +--------------------+---------+ # | Material Parameter | Value | # +====================+=========+ # | k | 6062 | # +--------------------+---------+ # | d_0 | 0.0025 | # +--------------------+---------+ # | lambda_s | 0.0804 | # +--------------------+---------+ # | d_s | 0.034 | # +--------------------+---------+ # # +--------------------------+---------+ # | Regularisation Parameter | Value | # +==========================+=========+ # | alpha | 10**10 | # +--------------------------+---------+ # | step_size | 0.33 | # +--------------------------+---------+ # | max_iterations | 400 | # +--------------------------+---------+ # | rel_conv_crit | 0.009 | # +--------------------------+---------+ # # define the parameters to generate the solver mesh and interpolate the piv mesh onto it material_parameters = {'k': 6062.0, 'd_0': 0.0025, 'lambda_s': 0.0804, 'd_s': 0.03} solve_parameters = {'alpha': 10**10, 'step_size': 0.33, 'max_iterations': 400, 'rel_conv_crit': 0.009} # iterate over all the results objects for result in results: result.material_parameters = material_parameters result.solve_parameters = solve_parameters for M in result.solvers: # set the material model M.set_material_model(saenopy.materials.SemiAffineFiberMaterial( material_parameters["k"], material_parameters["d_0"], material_parameters["lambda_s"], material_parameters["d_s"], )) # find the regularized force solution M.solve_regularized(alpha=solve_parameters["alpha"], step_size=solve_parameters["step_size"], max_iterations=solve_parameters["max_iterations"], rel_conv_crit=solve_parameters["rel_conv_crit"], verbose=True) # save the forces result.save() # %% # Display Results # ---------------------- # # .. figure:: ../images/examples/single_cell_tfm/liver_fibroblast_workflow.png # # The reconstructed force field (right) generates a reconstructed deformation field (middle) # that recapitulates the measured matrix deformation field (left). The overall cell contractility is # calculated as all forcecomponents pointing to the force epicenter. #