Module nlisim.modules.liver

Classes

class Liver (config: SimulationConfig)

Liver

Expand source code

class Liver(ModuleModel):
    """Liver"""

    name = 'liver'
    StateClass = LiverState

    def initialize(self, state: State) -> State:
        liver: LiverState = state.liver

        # config file values
        liver.hep_slope = self.config.getfloat('hep_slope')  # units: aM
        liver.hep_intercept = self.config.getfloat('hep_intercept')  # units: aM
        liver.il6_threshold = self.config.getfloat('il6_threshold')  # units: aM
        liver.threshold_log_hep = self.config.getfloat('threshold_log_hep')

        # computed values
        liver.threshold_hep = math.pow(10, liver.threshold_log_hep)

        return state

    def advance(self, state: State, previous_time: float) -> State:
        """Advance the state by a single time step."""
        from nlisim.modules.hepcidin import HepcidinState
        from nlisim.modules.il6 import IL6State
        from nlisim.modules.transferrin import TransferrinState
        from nlisim.util import TissueType

        liver: LiverState = state.liver
        transferrin: TransferrinState = state.transferrin
        il6: IL6State = state.il6
        hepcidin: HepcidinState = state.hepcidin
        molecules: MoleculesState = state.molecules
        voxel_volume: float = state.voxel_volume

        # interact with IL6
        mask = state.lung_tissue != TissueType.AIR
        global_il6_concentration = np.mean(il6.grid[mask]) / (
            2 * voxel_volume
        )  # div 2: serum, units: aM
        if global_il6_concentration > liver.il6_threshold:
            log_hepcidin = liver.hep_intercept + liver.hep_slope * (
                math.log(global_il6_concentration, 10)
            )
        else:
            log_hepcidin = float('-inf')

        # interact with transferrin
        tf = transferrin.tf_intercept + transferrin.tf_slope * max(
            transferrin.threshold_log_hep, log_hepcidin
        )  # units: aM
        rate_tf = turnover_rate(
            x=transferrin.grid['Tf'],
            x_system=tf * transferrin.default_apotf_rel_concentration * voxel_volume,
            base_turnover_rate=molecules.turnover_rate,
            rel_cyt_bind_unit_t=molecules.rel_cyt_bind_unit_t,
        )
        rate_tf_fe = turnover_rate(
            x=transferrin.grid['TfFe'],
            x_system=tf * transferrin.default_tffe_rel_concentration * voxel_volume,
            base_turnover_rate=molecules.turnover_rate,
            rel_cyt_bind_unit_t=molecules.rel_cyt_bind_unit_t,
        )
        rate_tf_fe2 = turnover_rate(
            x=transferrin.grid['TfFe2'],
            x_system=tf * transferrin.default_tffe2_rel_concentration * voxel_volume,
            base_turnover_rate=molecules.turnover_rate,
            rel_cyt_bind_unit_t=molecules.rel_cyt_bind_unit_t,
        )
        transferrin.grid['Tf'] *= rate_tf
        transferrin.grid['TfFe'] *= rate_tf_fe
        transferrin.grid['TfFe2'] *= rate_tf_fe2

        # interact with hepcidin
        system_concentration = (
            liver.threshold_hep
            if log_hepcidin == float('-inf') or log_hepcidin > liver.threshold_log_hep
            else math.pow(10.0, log_hepcidin)
        )
        hepcidin.grid *= turnover_rate(
            x=hepcidin.grid,
            x_system=system_concentration * voxel_volume,
            base_turnover_rate=molecules.turnover_rate,
            rel_cyt_bind_unit_t=molecules.rel_cyt_bind_unit_t,
        )

        return state

Ancestors

• ModuleModel

Methods

def advance(self, state: State, previous_time: float) ‑> State

Advance the state by a single time step.

Expand source code

def advance(self, state: State, previous_time: float) -> State:
    """Advance the state by a single time step."""
    from nlisim.modules.hepcidin import HepcidinState
    from nlisim.modules.il6 import IL6State
    from nlisim.modules.transferrin import TransferrinState
    from nlisim.util import TissueType

    liver: LiverState = state.liver
    transferrin: TransferrinState = state.transferrin
    il6: IL6State = state.il6
    hepcidin: HepcidinState = state.hepcidin
    molecules: MoleculesState = state.molecules
    voxel_volume: float = state.voxel_volume

    # interact with IL6
    mask = state.lung_tissue != TissueType.AIR
    global_il6_concentration = np.mean(il6.grid[mask]) / (
        2 * voxel_volume
    )  # div 2: serum, units: aM
    if global_il6_concentration > liver.il6_threshold:
        log_hepcidin = liver.hep_intercept + liver.hep_slope * (
            math.log(global_il6_concentration, 10)
        )
    else:
        log_hepcidin = float('-inf')

    # interact with transferrin
    tf = transferrin.tf_intercept + transferrin.tf_slope * max(
        transferrin.threshold_log_hep, log_hepcidin
    )  # units: aM
    rate_tf = turnover_rate(
        x=transferrin.grid['Tf'],
        x_system=tf * transferrin.default_apotf_rel_concentration * voxel_volume,
        base_turnover_rate=molecules.turnover_rate,
        rel_cyt_bind_unit_t=molecules.rel_cyt_bind_unit_t,
    )
    rate_tf_fe = turnover_rate(
        x=transferrin.grid['TfFe'],
        x_system=tf * transferrin.default_tffe_rel_concentration * voxel_volume,
        base_turnover_rate=molecules.turnover_rate,
        rel_cyt_bind_unit_t=molecules.rel_cyt_bind_unit_t,
    )
    rate_tf_fe2 = turnover_rate(
        x=transferrin.grid['TfFe2'],
        x_system=tf * transferrin.default_tffe2_rel_concentration * voxel_volume,
        base_turnover_rate=molecules.turnover_rate,
        rel_cyt_bind_unit_t=molecules.rel_cyt_bind_unit_t,
    )
    transferrin.grid['Tf'] *= rate_tf
    transferrin.grid['TfFe'] *= rate_tf_fe
    transferrin.grid['TfFe2'] *= rate_tf_fe2

    # interact with hepcidin
    system_concentration = (
        liver.threshold_hep
        if log_hepcidin == float('-inf') or log_hepcidin > liver.threshold_log_hep
        else math.pow(10.0, log_hepcidin)
    )
    hepcidin.grid *= turnover_rate(
        x=hepcidin.grid,
        x_system=system_concentration * voxel_volume,
        base_turnover_rate=molecules.turnover_rate,
        rel_cyt_bind_unit_t=molecules.rel_cyt_bind_unit_t,
    )

    return state

Inherited members

• ModuleModel:
  • StateClass
  • construct
  • finalize
  • initialize
  • name
  • section
  • summary_stats
  • time_step
  • visualization_data

class LiverState (*, global_state: State)

Base type intended to store the state for simulation modules.

This class contains serialization support for basic types (float, int, str, bool) and numpy arrays of those types. Modules containing more complicated state must override the serialization mechanism with custom behavior.

Method generated by attrs for class LiverState.

Expand source code

class LiverState(ModuleState):
    hep_slope: float
    hep_intercept: float
    il6_threshold: float  # units: aM
    threshold_log_hep: float
    threshold_hep: float

Ancestors

• ModuleState

Class variables

var hep_intercept : float

var hep_slope : float

var il6_threshold : float

var threshold_hep : float

var threshold_log_hep : float

Inherited members

• ModuleState:
  • load_attribute
  • load_state
  • save_attribute
  • save_state