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set_params_preg.py
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set_params_preg.py
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# this is to set the parameters for the pregnancy model for the rat
# note that diabetes and unx has not been characterized so then there are no diabetes/unx options in this file
import re
from defs import *
from values import *
import time
# pick out compartment IDs. E.g. given label=Area_Lumen_Cell, it would return
# (0,1) for (lumen, cell)
def get_interface_id(label):
tmp = (label).split('_')
if len(tmp)==3: # only have two compartment IDs
ind1,ind2 = compart_id[tmp[1]],compart_id[tmp[2]]
return ind1, ind2
elif len(tmp)==4: # solute ID, followed by two compartment IDs
sid,ind1,ind2 = solute_id[tmp[1]],compart_id[tmp[2]],compart_id[tmp[3]]
return sid,ind1,ind2
# for coupled transpoters
# pick out solute IDs, compartment IDs, and coefficients
def get_coupled_id(label):
tmp = (label).split('_')
# print(tmp)
sid1,sid2 = solute_id[tmp[3]],solute_id[tmp[4]]
ind1,ind2 = compart_id[tmp[1]],compart_id[tmp[2]]
if len(tmp)==5: # only involves 2 solutes
return ind1,ind2,sid1,sid2
elif len(tmp)==6: # involves 3 solutes
sid3 = solute_id[tmp[5]]
return ind1,ind2,sid1,sid2,sid3
else:
print("Wrong label",tmp)
# is str_short at the beginning of str_long?
# case insensitive
def compare_string_prefix(str_long,str_short):
return (str_long.lower())[:len(str_short)] == str_short.lower()
def compare_sex(sex, cell):
if sex.lower() == 'male' or sex.lower() == 'female':
return cell.sex.lower() == sex.lower()
else:
return True
def read_params_preg(cell,filename,j):
file = open(filename,'r')
cell.segment=filename[12:-16]
# error messages
if cell.preg == 'non':
print('cell.preg: ' + cell.preg)
raise Exception('read_params_preg is for pregnant model')
if cell.diabete != 'Non':
print('cell.diabete: ' + cell.diabete)
raise Exception('diabetes during pregnancy has not been done yet')
if cell.unx == 'Y':
print('cell.unx:' + cell.unx)
raise Exception('unx has not been done for pregnancy yet')
if cell.species != 'rat':
print('cell.species: ' + cell.species)
raise Exception('pregnancy only done for rat, human model not set up yet')
line = file.readline()
while (line):
line = line.replace('\t',' ')
terms = line.split(' ')
if line[0][0]!='#':
id = terms[0] #re.findall(r'[A-Za-z_]+', line)
sex = id.split('_')[-1].lower()
if compare_sex(sex, cell):
id = id.replace('_male', '')
id = id.replace('_female', '')
else:
line = file.readline()
continue;
# Skip over the label, which may contain numbers like in HCO3
first_space_pos = line.index(' ')
num = re.findall(r'-?\d+\.?\d*[Ee]?[+-]?\d*', line[first_space_pos:len(line)])
if num: # if this line is numerical parameter
value = float(num[0])
if id.lower() == "Sex".lower():
find = re.findall("Female".lower(), terms[-1].lower())
if find:
cell.sex = "Female".lower()
# Diameter:
elif compare_string_prefix(id,"Diameter"):
# pregnant diameter
preg_rat = 1.0 # reset preg_rat
if cell.segment == 'PT' or cell.segment == 'S3':
if cell.preg == 'mid':
preg_rat = 1.07
elif cell.preg == 'late':
preg_rat = 1.07
else:
if cell.preg == 'mid':
preg_rat = 1.05
elif cell.preg == 'late':
preg_rat = 1.05
if cell.type != 'sup':
if cell.preg == 'mid':
preg_rat = preg_rat*1.03
elif cell.preg == 'late':
preg_rat = preg_rat*1.03
cell.diam = value*preg_rat
# Length:
elif compare_string_prefix(id,"Length"):
# pregnant PT length
if cell.segment == 'PT' or cell.segment == 'S3':
if cell.preg == 'mid':
cell.len = value*1.15
elif cell.preg == 'late':
cell.len = value*1.165
# juxtamedullary segments lengths
elif cell.segment == 'LDL' or cell.segment == 'LAL':
if cell.type == 'jux1':
looplen = 0.2
elif cell.type == 'jux2':
looplen = 0.4
elif cell.type == 'jux3':
looplen = 0.6
elif cell.type == 'jux4':
looplen = 0.8
elif cell.type == 'jux5':
looplen = 1.0
cell.len = value*looplen
else:
cell.len = value
if cell.type != 'sup' and cell.species == 'rat':
if cell.segment == 'cTAL':
if cell.sex == 'male':
cell.len = 0.05
elif cell.sex == 'female':
cell.len = 0.05*0.9 #updated female
elif cell.segment == 'CNT':
if cell.sex == 'male':
cell.len = 0.3
elif cell.sex == 'female':
cell.len = 0.3*0.9 #updated female
if cell.type != 'sup' and cell.species == 'hum':
if cell.segment == 'cTAL':
if cell.sex == 'male':
cell.len = 0.125
elif cell.sex == 'female':
cell.len = 0.125
elif cell.segment == 'CNT':
if cell.sex == 'male':
cell.len = 0.6
elif cell.sex == 'female':
cell.len = 0.6
# Total number of cells:
elif compare_string_prefix(id,"Total"):
cell.total = value
# Luminal pressure:
elif compare_string_prefix(id,"Pressure"):
cell.pres[0] = value
if cell.type !='sup' and cell.segment == 'PT' and cell.species == 'rat':
if cell.preg == 'mid':
cell.pres[0] = 12.75
elif cell.preg == 'late':
cell.pres[0] = 12.75
# pH:
elif compare_string_prefix(id,"pH"):
for i in range(6):
cell.pH[i] = num[i]
# Surface area multiplication factor:
elif compare_string_prefix(id,"Area"):
ind1,ind2 = get_interface_id(id)
cell.area[ind1][ind2] = value
cell.area[ind2][ind1] = value # symmetry
cell.area_init[ind1][ind2] = value
cell.area_init[ind2][ind1] = value
if cell.type != 'sup' and cell.species == 'rat':
if cell.segment == 'PT' or cell.segment == 'S3':
cell.area[ind1][ind2] = 1.75*cell.area[ind1][ind2]
cell.area[ind2][ind1] = cell.area[ind1][ind2]
# Water permeabilities:
elif compare_string_prefix(id,"Pf"):
ind1,ind2 = get_interface_id(id)
# Units of dimensional water flux (in 'value'): cm3/s/cm2 epith
# Non-dimensional factor for water flux: (Pfref)*Vwbar*Cref
# Calculate non-dimensional dLPV = Pf*Vwbar*Cref / (Pfref*Vwbar*Cref)
# dLPV = Pf/Pfref
preg_rat = 1.0 #reset to 1.0, will change if needed
HT_rat = 1.0
if cell.preg != 'non':
# pregnancy water perm (transcellular)
if ind1 == 0 and ind2 == 1:
if cell.segment == 'PT' or cell.segment == 'S3':
if cell.preg == 'mid':
preg_rat = 1.0
elif cell.preg == 'late':
preg_rat = 1.0
elif cell.segment == 'SDL':
if cell.preg == 'mid':
preg_rat = 1.1
elif cell.preg == 'late':
preg_rat = 1.5
elif cell.segment == 'LDL':
if cell.preg == 'mid':
preg_rat = 1.1
elif cell.preg == 'late':
preg_rat = 1.5
elif cell.segment == 'CCD':
if cell.preg == 'mid':
preg_rat = 1.4
elif cell.preg == 'late':
preg_rat = 1.4
if cell.HT != 'N':
HT_rat = 1.0
preg_rat = preg_rat*HT_rat
elif cell.segment == 'OMCD':
if cell.preg == 'mid':
preg_rat = 1.4
elif cell.preg == 'late':
preg_rat = 1.4
if cell.HT != 'N':
HT_rat = 1.0
preg_rat = preg_rat*HT_rat
elif cell.segment == 'IMCD':
if cell.preg == 'mid':
preg_rat = 1.8
elif cell.preg == 'late':
preg_rat = 1.8
if cell.HT != 'N':
HT_rat = 1.0
preg_rat = preg_rat*HT_rat
elif ind1 == 1:
if ind2 == 4 or ind2 == 5:
if cell.segment == 'PT' or cell.segment == 'S3':
if cell.preg == 'mid':
preg_rat = 1.0
elif cell.preg == 'late':
preg_rat = 1.0
elif cell.segment == 'SDL':
if cell.preg == 'mid':
preg_rat = 1.1
elif cell.preg == 'late':
preg_rat = 1.5
elif cell.segment == 'LDL':
if cell.preg == 'mid':
preg_rat = 1.1
elif cell.preg == 'late':
preg_rat = 1.5
elif cell.segment == 'CCD':
if cell.preg == 'mid':
preg_rat = 1.4
elif cell.preg == 'late':
preg_rat = 1.4
if cell.HT != 'N':
HT_rat = 0.8
preg_rat = preg_rat*HT_rat
elif cell.segment == 'OMCD':
if cell.preg == 'mid':
preg_rat = 1.4
elif cell.preg == 'late':
preg_rat = 1.4
if cell.HT != 'N':
HT_rat = 0.8
preg_rat = preg_rat*HT_rat
elif cell.segment == 'IMCD':
if cell.preg == 'mid':
preg_rat = 1.8
elif cell.preg == 'late':
preg_rat = 1.8
if cell.HT != 'N':
HT_rat = 0.8
preg_rat = preg_rat*HT_rat
cell.dLPV[ind1][ind2] = value/Pfref*preg_rat
#print('water permeability')
#print(ind1, ind2, cell.dLPV[ind1][ind2],preg_rat)
# symmetry
cell.dLPV[ind2][ind1] = value/Pfref*preg_rat
if cell.segment == 'SDL' and cell.type == 'sup':
if j>=0.46*cell.total:
cell.dLPV[0,1]=0.00*cell.dLPV[0,1]
cell.dLPV[0,4]=0.00*cell.dLPV[0,4]
elif cell.segment == 'LDL':
if cell.sex == 'male':
if j>=0.4*cell.total:
cell.dLPV[0,1]=0.00*cell.dLPV[0,1]
cell.dLPV[0,4]=0.00*cell.dLPV[0,4]
elif cell.sex == 'female':
if j>=0.5*cell.total:
cell.dLPV[0,1]=0.00*cell.dLPV[0,1]
cell.dLPV[0,4]=0.00*cell.dLPV[0,4]
if cell.segment == 'CNT' and cell.type !='sup':
if cell.sex == 'female':
cell.dLPV = cell.dLPV*4/3
# Reflection coefficients:
elif compare_string_prefix(id,"sig"):
sid,ind1,ind2 = get_interface_id(id)
cell.sig[sid][ind1][ind2] = value
# symmetry
cell.sig[sid][ind2][ind1] = value
cell.sig[sid][4][5] = 0.0
cell.sig[sid][5][4] = 0.0
# Membrane solute permeabilities:
elif compare_string_prefix(id,"perm"):
sid,ind1,ind2 = get_interface_id(id)
cell.h[sid][ind1][ind2] = value*1.0e-5/href
# Symmetry:
cell.h[sid][ind2][ind1] = value*1.0e-5/href
# Same permeability on basolateral membrane (around bath or LIS):
if ind1==1 and ind2==5:
cell.h[sid][ind1][4] = value*1.0e-5/href
cell.h[sid][4][ind1] = value*1.0e-5/href
elif ind1==1 and ind2==4:
cell.h[sid][ind1][5] = value*1.0e-5/href
cell.h[sid][5][ind1] = value*1.0e-5/href
elif ind1==2 and ind2==4:
cell.h[sid][ind1][5] = value*1.0e-5/href
elif ind1==3 and ind2==4:
cell.h[sid][ind1][5] = value*1.0e-5/href
if cell.segment == 'OMCD':
cell.h[sid][0][3] = 0.0
cell.h[sid][3][4] = 0.0
cell.h[sid][3][5] = 0.0
if cell.segment == 'IMCD':
if cell.sex == 'male':
if j>3*cell.total/4-1:
cell.h[8,0,1] = 300.0*1.0e-5/href
elif cell.sex == 'female':
if j>2*cell.total/3-1:
cell.h[8,0,1] = 300.0*1.0e-5/href
if cell.segment == 'LDL':
if cell.sex == 'male':
if j>=0.4*cell.total:
cell.h[0,0,1]=80.0
cell.h[0,0,4]=80.0
cell.h[1,0,1]=100.0
cell.h[1,0,4]=100.0
cell.h[2,0,1]=80.0
cell.h[2,0,4]=80.0
cell.h[3,0,1]=20.0
cell.h[3,0,4]=20.0
cell.h[10,0,1]=20.0
cell.h[10,0,4]=20.0
cell.h[8,0,1]=80.0 #80
cell.h[8,0,4]=80.0 #80
elif cell.sex == 'female':
if j>=0.5*cell.total:
cell.h[0,0,1]=40.0
cell.h[0,0,4]=80.0
cell.h[1,0,1]=100.0
cell.h[1,0,4]=100.0
cell.h[2,0,1]=40.0
cell.h[2,0,4]=80.0
cell.h[3,0,1]=20.0
cell.h[3,0,4]=20.0
cell.h[10,0,1]=20.0
cell.h[10,0,4]=20.0
cell.h[8,0,1]=80.0
cell.h[8,0,4]=80.0
# K secretion
if cell.segment == 'DCT':
if j>0.66*cell.total:
#DCT2
if cell.preg == 'late':
preg_rat = 0.55
if cell.HT != 'N':
HT_rat = 0.3
preg_rat = preg_rat*HT_rat
cell.h[1,0,1] = 0.6*preg_rat
elif cell.preg == 'mid':
preg_rat = 0.65
if cell.HT != 'N':
HT_rat = 0.3
preg_rat = preg_rat*HT_rat
cell.h[1,0,1] = 0.6*preg_rat
elif cell.segment == 'CNT':
if cell.preg == 'late':
preg_rat = 0.55
if cell.HT != 'N':
HT_rat = 0.3
preg_rat = preg_rat*HT_rat
cell.h[1,0,1] = 8.0*preg_rat
elif cell.preg == 'mid':
preg_rat = 0.65
if cell.HT != 'N':
HT_rat = 0.3
preg_rat = preg_rat*HT_rat
cell.h[1,0,1] = 8.0*preg_rat
elif cell.segment == 'CCD':
if cell.preg == 'late':
preg_rat = 0.75
cell.h[1,0,1] = 1.4*preg_rat
elif cell.preg == 'mid':
preg_rat = 0.775
cell.h[1,0,1] = 1.4*preg_rat
elif cell.segment == 'OMCD':
if cell.preg == 'late':
preg_rat = 0.85
cell.h[1,0,1] = 2.4*preg_rat
elif cell.preg == 'mid':
preg_rat = 0.875
cell.h[1,0,1] = 2.4*preg_rat
# Coupled transporters:
elif compare_string_prefix(id,"coupled"):
# retrieve interface and solute id
vals = get_coupled_id(id)
newdLA = coupled_transport()
newdLA.perm = value / (href*Cref)
newdLA.membrane_id = [vals[0],vals[1]]
coef = [] # retrieve coupling coefficients
for i in range(1,len(num)):
coef.append(int(num[i]))
newdLA.coef = coef
newdLA.solute_id = vals[2:len(vals)]
# NaPi2
if newdLA.solute_id == (0,7):
if cell.segment == 'PT' or cell.segment == 'S3':
if cell.preg == 'mid':
if cell.HT != 'N':
HT_rat = 0.85
newdLA.perm = HT_rat*0.9*newdLA.perm
else:
newdLA.perm = 0.9*newdLA.perm
elif cell.preg == 'late':
newdLA.perm = 0.85*newdLA.perm
else:
print('segment: ' + cell.segment)
raise Exception('NaPi2 in pregnancy not characterized for this segment')
# K-Cl cotransporter
elif newdLA.solute_id == (1,2):
if cell.segment == 'PT' or cell.segment == 'S3':
if cell.preg == 'mid':
newdLA.perm = 1.35*newdLA.perm
elif cell.preg == 'late':
newdLA.perm = 1.3*newdLA.perm
elif cell.segment == 'DCT':
if cell.preg == 'mid':
newdLA.perm = 1.4*newdLA.perm
elif cell.preg == 'late':
newdLA.perm = 1.3*newdLA.perm
elif cell.segment == 'IMCD':
if cell.preg == 'mid':
newdLA.perm = 1.4*newdLA.perm
elif cell.preg == 'late':
newdLA.perm = 1.3*newdLA.perm
else:
print('segment: '+cell.segment)
raise Exception('K-Cl coupled transporter not characterized for pregnancy in this segment')
#Na-Cl cotransporter
elif newdLA.solute_id == (0,2):
if cell.segment == 'OMCD':
if cell.preg == 'mid':
newdLA.perm = 1.15*newdLA.perm
elif cell.preg == 'late':
newdLA.perm = 1.0*newdLA.perm
elif cell.segment == 'IMCD':
if cell.preg == 'mid':
newdLA.perm = 1.15*newdLA.perm
elif cell.preg == 'late':
newdLA.perm = 1.0*newdLA.perm
else:
print('segment: ' + cell.segment)
raise Exception('Na-Cl coupled transporter not characterized for pregnancy in this segment')
cell.dLA.append(newdLA)
# Specific transporters:
elif compare_string_prefix(id,"transport"):
tmp = (id).split('_')
ind1,ind2 = compart_id[tmp[1]],compart_id[tmp[2]]
newTransp = transporter()
newTransp.membrane_id = [ind1,ind2]
newTransp.type = tmp[3]
newTransp.act = value/(href*Cref)
#print('transporter')
#print(newTransp.membrane_id,newTransp.type,newTransp.act)
if cell.type != 'sup' and cell.sex == 'female' and cell.species == 'rat':
if cell.segment == 'mTAL' or cell.segment == 'cTAL':
if newTransp.type == 'NKCC2A' or newTransp.type == 'NKCC2B' or newTransp.type == 'NKCC2F' or newTransp.type == 'NaKATPase':
newTransp.act = 1.5*value/(href*Cref)
elif newTransp.type == 'KCC4':
newTransp.act = 2.0*value/(href*Cref)
preg_rat = 1.0
HT_rat = 1.0
# pregnant model values
if newTransp.type == 'NHE3':
# PCT, S3, mTAL, cTAL, DCT
if cell.segment == 'PT' or cell.segment == 'S3':
if cell.preg == 'mid':
preg_rat = 1.4
elif cell.preg == 'late':
preg_rat = 1.2
if cell.HT != 'N':
HT_rat = 0.82
preg_rat = HT_rat*preg_rat
elif cell.segment == 'mTAL':
if cell.preg == 'mid':
preg_rat = 1.2
elif cell.preg == 'late':
preg_rat = 1.175
if cell.HT != 'N':
HT_rat = 0.82
preg_rat = HT_rat*preg_rat
elif cell.segment == 'cTAL' or cell.segment == 'DCT':
if cell.preg == 'mid':
preg_rat = 1.2
elif cell.preg == 'late':
preg_rat = 1.175
if cell.HT != 'N':
HT_rat = 1.0
preg_rat = HT_rat*preg_rat
else:
print('segment: ' + cell.segment)
raise Exception('NHE3 activity not done for pregnancy in this segment')
elif newTransp.type == 'NaKATPase':
if cell.segment == 'PT' or cell.segment == 'S3' or cell.segment == 'cTAL':
if cell.preg == 'mid':
preg_rat = 0.745
elif cell.preg == 'late':
preg_rat = 0.65
if cell.HT != 'N':
HT_rat = 1.0
preg_rat = HT_rat*preg_rat
elif cell.segment == 'DCT':
if cell.preg == 'mid':
preg_rat = 0.8
elif cell.preg == 'late':
preg_rat = 0.75
elif cell.segment == 'CNT':
if cell.preg == 'mid':
preg_rat = 0.8
elif cell.preg == 'late':
preg_rat = 0.775
elif cell.segment == 'mTAL':
if cell.preg == 'mid':
preg_rat = 1.2
elif cell.preg == 'late':
preg_rat = 1.0
if cell.HT != 'N':
HT_rat = 0.70
preg_rat = HT_rat*preg_rat
elif cell.segment == 'CCD':
if cell.preg == 'mid':
preg_rat = 0.8
elif cell.preg == 'late':
preg_rat = 0.75
elif cell.segment == 'IMCD' or cell.segment == 'OMCD':
if cell.preg == 'mid':
preg_rat = 1.2
elif cell.preg == 'late':
preg_rat = 1.0775
else:
print('segment: ' + cell.segment)
raise Exception('NaKATPase activity not done for pregnancy in segment')
elif newTransp.type == 'NKCC2A' or newTransp.type == 'NKCC2B' or newTransp.type == 'NKCC2F':
if cell.segment == 'mTAL':
if cell.preg == 'mid':
preg_rat = 1.155
elif cell.preg == 'late':
preg_rat = 1.5
if cell.HT != 'N':
HT_rat = 0.7
preg_rat = HT_rat*preg_rat
if cell.inhib == 'NKCC2-70':
preg_rat = preg_rat*(1-0.7)
if cell.inhib == 'NKCC2-100':
preg_rat = preg_rat*(1-1)
elif cell.segment == 'cTAL':
if cell.preg == 'mid':
preg_rat = 1.15
elif cell.preg == 'late':
preg_rat = 1.5
if cell.inhib == 'NKCC2-70':
preg_rat = preg_rat*(1-0.7)
if cell.inhib == 'NKCC2-100':
preg_rat = preg_rat*(1-1)
if cell.HT != 'N':
HT_rat = 1.75
preg_rat = HT_rat*preg_rat
else:
print('segment: ' + cell.segment)
raise Exception('NKCC2 activity not done for pregnancy in this segment')
elif newTransp.type == 'KCC4':
if cell.preg == 'mid':
preg_rat = 1.35
elif cell.preg == 'late':
preg_rat = 1.3
elif newTransp.type == 'NCC':
if cell.preg == 'mid':
preg_rat = 1.0
if cell.inhib == 'NCC-70':
preg_rat = preg_rat*(1-0.7)
elif cell.inhib == 'NCC-100':
preg_rat = preg_rat*(1-1)
elif cell.preg == 'late':
preg_rat = 0.45
if cell.HT != 'N':
HT_rat = 1.95
preg_rat = preg_rat*HT_rat
elif newTransp.type == 'ENaC':
if cell.preg == 'mid':
preg_rat = 2.075
elif cell.preg == 'late':
preg_rat = 2.15
if cell.HT != 'N':
HT_rat = 1.45
preg_rat = preg_rat*HT_rat
if cell.inhib == 'ENaC-70':
preg_rat = preg_rat*(1-0.7)
if cell.inhib == 'ENaC-100':
preg_rat = preg_rat*(1-1)
elif newTransp.type == 'HKATPase':
if cell.preg == 'mid':
preg_rat = 2.25
elif cell.preg == 'late':
preg_rat = 2.75
elif newTransp.type == 'HATPase':
if cell.preg == 'mid':
preg_rat = 1.0
elif cell.preg == 'late':
preg_rat = 1.0
elif newTransp.type == 'Pendrin':
if cell.preg == 'mid':
preg_rat = 1.65
elif cell.preg == 'late':
preg_rat = 1.7
elif newTransp.type == 'NHE1':
if cell.preg == 'mid':
preg_rat = 0.9
elif cell.preg == 'late':
preg_rat = 0.9
elif newTransp.type == 'AE1':
if cell.preg == 'mid':
preg_rat = 1.0
elif cell.preg == 'late':
preg_rat = 1.0
else:
preg_rat = 1.0
newTransp.act = preg_rat*newTransp.act
#print(cell.preg + 'pregnant transporter activity: ' + str(newTransp.act))
cell.trans.append(newTransp)
# Solute concentrations:
elif compare_string_prefix(id,"conc"):
tmp = (id).split('_')
cell.conc[solute_id[tmp[1]]][0] = float(num[0])
cell.conc[solute_id[tmp[1]]][1] = float(num[1])
cell.conc[solute_id[tmp[1]]][4] = float(num[2])
cell.conc[solute_id[tmp[1]]][5] = float(num[3])
if len(num) > 4:
cell.conc[solute_id[tmp[1]]][2] = float(num[4])
if len(num) > 5:
cell.conc[solute_id[tmp[1]]][3] = float(num[5])
# Reference impermeat concentration (for cell)
# or oncotic pressure for lumen/LIS/bath
elif compare_string_prefix(id,"cimpref"):
tmp = (id).split('_')
cell.cimpref[compart_id[tmp[1]]] = float(num[0])
# Impermeant properties
elif compare_string_prefix(id,"zimp"):
tmp = (id).split('_')
cell.zimp[compart_id[tmp[1]]] = float(num[0])
# Reference buffer concentrations (for cell):
elif compare_string_prefix(id,"cbuftot"):
tmp = (id).split('_')
cell.cbuftot[compart_id[tmp[1]]] = float(num[0])
# Rates used in HCO3/H2CO3 reaction:
elif compare_string_prefix(id,"dkd"):
tmp = (id).split('_')
cell.dkd[compart_id[tmp[1]]] = float(num[0])
elif compare_string_prefix(id,"dkh"):
tmp = (id).split('_')
cell.dkh[compart_id[tmp[1]]] = float(num[0])
# Reference volume flows:
elif compare_string_prefix(id,"volref"):
tmp = (id).split('_')
cell.volref[compart_id[tmp[1]]] = float(num[0])
# Actual volume flows:
elif compare_string_prefix(id,"vol"):
tmp = (id).split('_')
if cell.segment == 'PT' and cell.type == 'sup':
# SNGFR for sup nephrons
if compart_id[tmp[1]] == 0:
if cell.preg == 'mid':
cell.vol[0] = 0.0052 #0.004*1.3
elif cell.preg == 'late':
cell.vol[0] = 0.0048 #0.004*1.2
cell.vol_init[0] = cell.vol[0]
else:
cell.vol[compart_id[tmp[1]]] = float(num[0])
cell.vol_init[compart_id[tmp[1]]] = float(num[0])
elif cell.segment == 'PT' and cell.type != 'sup' and cell.species == 'rat':
# SNGFR for jux nephrons
if compart_id[tmp[1]] == 0:
if cell.preg == 'mid':
cell.vol[0] = 0.007224 #0.0056*1.29
elif cell.preg == 'late':
cell.vol[0] = 0.006664 #0.0056*1.19
cell.vol_init[0] = cell.vol[0]
else:
cell.vol[compart_id[tmp[1]]] = float(num[0])
cell.vol_init[compart_id[tmp[1]]] = float(num[0])
else:
cell.vol[compart_id[tmp[1]]] = float(num[0])
cell.vol_init[compart_id[tmp[1]]] = float(num[0])
# Membrane potential:
elif compare_string_prefix(id,"ep"):
tmp = (id).split('_')
cell.ep[compart_id[tmp[1]]] = float(num[0])
# Interstitial concentration parameters
# CM: cortico-medullary boundary; OI: outer-inner stripe boundary; Pap: papillary tip
# changes for altered concentrations (i.e., in pregnancy) are made in boundaryBath
elif compare_string_prefix(id,'cm'):
cell.cm = []
for i in num:
cell.cm.append(float(i))
elif compare_string_prefix(id,'oi'):
cell.oi = []
for i in num:
cell.oi.append(float(i))
elif compare_string_prefix(id,'pap'):
cell.pap = []
for i in num:
cell.pap.append(float(i))
# invalue keyword
# else:
# print("Wrong id",id)
# if not a comment line
line = file.readline()
# Updating the reflective coefficients at the LIS-Bath interface:
for i in range(NS):
cell.sig[i,4,5] = 0.0
cell.sig[i,5,4] = 0.0
file.close()