TOXICOLOGICAL SCIENCES 74, 416 – 436 (2003)
DOI: 10.1093/toxsci/kfg147
Predicting Neonatal Perchlorate Dose and Inhibition of Iodide Uptake
in the Rat during Lactation Using Physiologically-Based
Pharmacokinetic Modeling
Rebecca A. Clewell,* ,1 Elaine A. Merrill,* Kyung O. Yu,† Deirdre A. Mahle,‡ Teresa R. Sterner,§ Jeffrey W. Fisher,† ,2 and
Jeffery M. Gearhart‡
*Geo-Centers, Inc., Wright-Patterson AFB, Ohio 45433; †AFRL/HEST, Wright-Patterson AFB, Ohio 45433; ‡Mantech Environmental Technology, Inc.,
Dayton, Ohio 45437; and §Operational Technologies Corp., Dayton, Ohio 45432
Received March 5, 2003; accepted May 1, 2003
Perchlorate (ClO 4 ⴚ), a contaminant in drinking water, competitively inhibits active uptake of iodide (I –) into various tissues,
including mammary tissue. During postnatal development, inhibition of I – uptake in the mammary gland and neonatal thyroid
and the active concentration ClO 4 ⴚ in milk indicate a potentially
increased susceptibility of neonates to endocrine disruption. A
physiologically based pharmacokinetic (PBPK) model was developed to reproduce measured ClO 4 ⴚ distribution in the lactating
and neonatal rat and predict resulting effects on I – kinetics from
competitive inhibition at the sodium iodide symporter (NIS). Kinetic I – and ClO 4 ⴚ behavior in tissues with NIS (thyroid, stomach,
mammary gland, and skin) was simulated with multiple subcompartments, Michaelis-Menten (M-M) kinetics and competitive inhibition. Physiological and kinetic parameters were obtained from
literature and experiment. Systemic clearance and M-M parameters were estimated by fitting simulations to tissue and serum data.
The model successfully describes maternal and neonatal thyroid,
stomach, skin, and plasma, as well as maternal mammary gland
and milk data after ClO 4 ⴚ exposure (from 0.01 to 10 mg/kg-day
ClO 4 ⴚ) and acute radioiodide (2.1 to 33,000 ng/kg I –) dosing. The
model also predicts I – uptake inhibition in the maternal thyroid,
mammary gland, and milk. Model simulations predict a significant transfer of ClO 4 ⴚ through milk after maternal exposure;
approximately 50% to 6% of the daily maternal dose at doses
ranging from 0.01 to 10.0 mg ClO 4 ⴚ/kg-day, respectively. Comparison of predicted dosimetrics across life-stages in the rat indicates that neonatal thyroid I – uptake inhibition is similar to the
adult and approximately tenfold less than the fetus.
Key Words: PBPK model; lactation; perchlorate; iodide; inhibition; milk.
Perchlorate (ClO 4 ⫺), the soluble anion of ammonium and
potassium perchlorate, is a thyroid iodide uptake inhibitor
1
To whom correspondence should be addressed at present address: CIIT
Centers for Health Research, Six Davis Drive, Research Triangle Park, NC
27709-2137. Fax: (919) 558-1300. E-mail: [email protected].
2
Present address: The University of Georgia, Athens, GA.
Toxicological Sciences 74(2), © Society of Toxicology 2003; all rights reserved.
known to be present in several United States drinking water
sources, ranging in concentrations from less than 4 ppb to more
than 3700 ppm in some Las Vegas water samples (Motzer,
2001). Human health concerns arise from the fact that ClO 4 ⫺,
being similar in size and shape to iodide (I –), is able to bind to
the sodium-iodide symporter (NIS), thus reducing the amount
of iodide taken up into the thyroid. Thyroid hormones are
synthesized from I – in the thyroid and are responsible for
regulating metabolism. In the adult, lack of iodide causes
reduced thyroxine (T 4) and triiodothyronine (T 3) levels and can
eventually lead to hypothyroidism (Wolff, 1998). Furthermore,
since these hormones are required for normal physical and
mental development, exposure to thyroid inhibitors during the
period of rapid growth in late gestation and early infancy could
result in long-term consequences (Howdeshell, 2002; Porterfield, 1994). Congenital hypothyroidism and gestational iodide
deficiency are known to cause delayed development and, in
severe cases, lowered IQ, mental retardation, and even cretinism (Delange, 2000; Haddow et al., 1999; Howdeshell, 2002;
Klein et al., 1972; Porterfield, 1994). In the case of perchlorate
contamination of drinking water sources, the question is
whether ClO 4 ⫺ is capable of inducing these same developmental effects and at what level of exposure the fetus or infant may
be at risk of adverse effects.
In order to help answer these questions, several studies have
been conducted in rats involving chronic and short-term perchlorate exposure during gestation, lactation, and in adult
males at a variety of doses (Bekkedal et al., 2001; Mahle et al.,
2002, 2003; York et al., 1999, 2001; Yu et al., 2002). None of
the available studies show the same extent of adverse effects
from perchlorate exposure as are known to occur in iodide
deficiency. However, consolidating these various data sets into
a quantitative measure of risk to the perchlorate-exposed infant
is quite difficult due to the variations in study design, as well
as the rapid physical and biochemical changes taking place
during lactation and infancy. To incorporate these kinetic,
physiological, and biochemical data into a predictive tool for
perchlorate, iodide, and perchlorate-induced inhibition kinet-
416
PBPK ClO 4 ⫺ MODEL FOR RAT LACTATION
ics, a physiologically based pharmacokinetic (PBPK) model
was developed in the lactating and neonatal rat. Together with
the concurrent PBPK models developed for the male rat (Merrill et al., 2003), pregnant and fetal rat (Clewell et al., 2003),
and the adult human (Merrill et al., 2001), the models can be
used to compare internal dose metrics, such as ClO 4 ⫺ concentration in the serum across developmental life stages and species. Thus, the models provide a means for extrapolating predicted kinetics and measures of dose to the potentially more
sensitive and often overlooked subpopulation, the human fetus
and infant (Clewell and Gearhart, 2002a).
Although the hormone feedback system of the postnatal rat
is independent of the mother (Howdeshell, 2002; Potter et al.,
1959; Vigouroux and Rostaqui, 1980), the effect of maternal
perchlorate exposure is intricately tied to neonatal risk. In fact,
there are several unique factors that must be accounted for
when attempting to quantify risk to the nursing neonate. For
example, the lactating mammary gland contains active NIS that
concentrates iodide in the milk, ensuring an adequate supply of
iodide to the newborn. However, since ClO 4 ⫺ competitively
inhibits iodide binding to NIS, maternal exposure during lactation also inhibits iodide transfer in the milk, as has been
noted in several species including the rat, goat, rabbit, and cow
(Brown-Grant, 1957; Cline et al., 1969; Grosvenor, 1963;
Lengemann, 1965; Potter et al., 1959). It is also possible that
this binding of perchlorate to NIS, which inhibits iodide uptake, is responsible for concentration of ClO 4 ⫺ in milk. Intralaboratory studies have shown milk ClO 4 ⫺ levels to be consistently higher than the maternal plasma, and the neonate was
found to have significant blood ClO 4 ⫺ concentrations after
nursing from the exposed dams (Yu et al., 2001). Thus, the
infant would be at risk not only from the diminished iodide
intake from the milk, but also from the significant doses of
ClO 4 ⫺ received from the milk, and the resulting additional
inhibition of iodide uptake at the neonatal thyroid NIS. The
PBPK model described here is able to account for the changing
physiology of the lactating dam and pup, as well as the resulting impact of these physiological changes on experimentally
determined iodide and perchlorate kinetics in order to provide
a meaningful, quantitative estimate of two previously uncharacterized determinants of neonatal risk: the relative ClO 4 ⫺ dose
to maternal and neonatal rats, and the dose-response relationship between perchlorate exposure and iodide inhibition in the
maternal thyroid and milk. At this stage, the model includes
only a rudimentary description of endogenous I – kinetics and
incorporation into thyroid hormones, sufficient to reproduce
the kinetics of radioiodide.
MATERIALS AND METHODS
Supporting Experiments
All supporting experiments were performed on timed-pregnant rats and pups
of the Sprague-Dawley strain (Crl: CD, Charles River Laboratory, Raleigh,
NC). Animals were housed in individual light, heat, and humidity controlled
417
cages and were kept on a 12 h light/dark cycle with access to water and food
ad libitum. Euthanization was performed by CO 2 asphyxiation on either
postnatal day (PND) 5 or 10 and tissues were collected for analysis of ClO 4 ⫺
or radioiodide content using the methods described in Narayanan et al. (2003),
respectively. In all experiments, pup serum was pooled by sex within individual litters due to small sample volumes. Pup skin, gastrointestinal (GI) tract, GI
contents, and maternal tissues were analyzed individually. The animals used in
in-house studies were handled in accordance with the principles stated in the
Guide for the Care and Use of Laboratory Animals, National Research
Council, 1996, and the Animal Welfare Act of 1966, as amended.
Perchlorate drinking water study. Pregnant dams (n ⫽ 12 per group) were
given either deionized water or water containing perchlorate from gestational
day (GD) 2 through the day of sacrifice. Daily measurements of body weight
and water intake were taken to ensure consistent dosing at levels of 0.0, 0.01,
0.1, 1.0, and 10.0 mg ClO 4 ⫺/kg-day. Maternal serum, thyroid and milk, and
neonatal serum were collected from the PND 10 groups and analyzed for
ClO 4 ⫺ content. On PND 5, six of the dams from each dosing regimen were
given a tail vein injection of 33 ␮g/kg 125I – 2 h prior to sacrifice. Maternal and
neonatal serum, skin, GI contents and GI tract, as well as maternal thyroid and
mammary gland, were collected from these PND 5 rats and analyzed for ClO 4 ⫺
and 125I –. Thyroid hormones (free and total T 4 and T 3) and TSH were also
measured in the serum of PND 5 rats that were not dosed with radioiodide.
Radioiodide and inhibition kinetic studies. Lactating dams (six control,
six inhibition) were dosed via tail vein injection to 125I – (average dose ⫽ 2.10
ng/kg) on PND 10 and euthanized at 0.5, 2, 4, 8, and 24 h postdosing. Two h
prior to the administration of 125I –, dams from the inhibition group were given
a 1.0 mg/kg ClO 4 ⫺ iv and euthanized at 0.5, 1, 2, 4, 8, 12, and 24 h post- 125I –
dosing. This particular ClO 4 ⫺ dose was chosen to be large enough dose to
significantly affect iodide uptake, based on inhibition of thyroid iodide uptake
in the male rat (Merrill et al., 2003), while being lower than the dose required
to saturate the symporter, based on the drinking water study results (see Results
section below). Maternal and neonatal serum, skin, GI contents and GI tract,
and maternal thyroid and mammary gland tissue were collected from both
control and perchlorate dosed groups and analyzed for 125I – with a gamma
counter.
Direct pup radioiodide dosing. PND 10 Sprague-Dawley pups (n ⫽ 6)
were given a po gavage of 125I – (0.001mg/kg) in water. Pups and nursing dams
were euthanized at 0.5, 1, 2, 4, 8, and 24 h postdosing. Neonatal serum,
thyroid, skin, GI contents and GI tract, as well as maternal serum and thyroid
were harvested and analyzed for radioiodide content.
Model Structure
All model code was written in ACSL (Advanced Continuous Simulation
Language, Aegis Technologies Group, Inc., Huntsville, AL). The model structure is based on those of the male rat and gestation models for iodide and
perchlorate kinetics developed concurrently by Merrill et al. (2003) and
Clewell et al. (2003). The maternal model (Fig. 1A) consists of compartments
for plasma, thyroid, skin, GI, kidney, liver, fat, mammary gland and milk, plus
compartments for the combined slowly and richly perfused tissues. The thyroid, GI and mammary gland are described with three subcompartments
representing the stroma, follicle and colloid in the thyroid, the capillary bed, GI
tissue and GI contents in the GI, and the capillary blood, tissue, and milk in the
mammary gland. For iodide, additional compartments representing the organified (hormone-bound) iodine were included in the thyroid and serum (Fig. 1B).
Skin is described with two subcompartments, representing the capillary bed
and tissue. Active uptake into the thyroid follicle and colloid, as well as the
skin tissue, mammary gland, milk, and GI contents, was described with
Michaelis-Menten (M-M) type kinetics for saturable processes (bold arrows in
Fig. 1). Permeability area cross products and partition coefficients were used to
describe the passive movement of the anions (I – and ClO 4 ⫺) between the
capillary bed, tissue, and inner compartments (small arrows in Fig. 1), which
results from the inherent electrochemical gradients within these tissues (Chow
et al., 1969). The flow-limited kidney, liver, and fat compartments were
418
FIG. 1. (A) Schematic of perchlorate PBPK model for lactating dam (left)
and neonate (right). Model structure for
sister iodine model is similar. Differences are contained within the inset area
outlined with the dashed line. (B) Thyroid and serum compartments for radioiodide, with additional compartments for
the incorporation of iodide into hormones in the thyroid and secretion of the
hormones into the serum incorporated iodine compartment as is discussed in the
Methods section.
CLEWELL ET AL.
PBPK ClO 4 ⫺ MODEL FOR RAT LACTATION
described with partitions and blood flows. Plasma binding of the inorganic
anions (I – and ClO 4 ⫺) was simulated using a saturable term for association of
the anions to binding sites in the plasma and a first order clearance rate for
dissociation from plasma binding sites. Urinary clearance and transfer of
anions between the dam and pup were represented by first order clearance
rates.
Due to the short time frame of the radioiodide experiments, the kinetic
behavior of total radioiodine was assumed to behave as free iodide in all
compartments other than the thyroid and plasma. Inorganic iodide and perchlorate were then modeled in the same manner, based on the similar size and
charge of the ions and their shared affinity for NIS (Wolff, 1998). The thyroid,
skin, GI and mammary gland contain active NIS and were therefore defined
separately in the structure of the model (Kotani et al., 1998; Spitzweg et al.,
1998). The thyroid, mammary gland, milk, skin and GI contents have also been
found to maintain higher concentrations of ClO 4 ⫺ and I – than the plasma
(Brown-Grant, 1961; Brown-Grant and Pethes, 1959; Chow et al., 1969; Halmi
and Stuelke, 1959; Wolff, 1998; Zeghal et al., 1995). Although other tissues,
such as the salivary gland, ovary, and choroid plexus, are also known to
sequester iodide and perchlorate in the rat and human (Brown-Grant, 1961;
Honour et al., 1952; Spitzweg et al., 1998), the small amounts of anions
present in these tissues do not affect plasma concentrations. These tissues were
therefore combined in the richly or slowly perfused compartments.
In order to describe free thyroidal iodide, it was necessary to account for the
incorporation of iodide into hormones in the thyroid and the secretion of this
incorporated iodine into the blood. Our goal was to describe this process with
enough detail to predict time course data, while keeping the model as parsimonious as possible. Thus, thyroid hormone production, or the incorporation
of iodide into hormones, is described using a first order clearance (ClProdc i)
of inorganic iodide from the thyroid follicle to the incorporated thyroid iodine
compartment. Secretion of the incorporated iodine into the plasma is also
described with a first order clearance (ClSecrc i) from the incorporated thyroid
iodine compartment to the incorporated plasma iodine compartment (Fig. 1B).
It was not necessary to include a description of hormone incorporation in the
perchlorate model, since ClO 4 ⫺ is not organified or metabolized in vivo (Anbar
et al., 1959).
The incorporated plasma iodine compartment represents combined plasma
hormonal iodine, including free T 3 and T 4 as well as protein bound T 3 and T 4,
but does not attempt to predict individual hormone kinetics. Studies of iodine
distribution from dietary intake suggest that the majority (⬎80%) of serum
iodine is, in fact, incorporated into hormones or bound to plasma proteins
(Stolc et al., 1973b). In contrast, studies in our laboratory found that inorganic
iodide accounts for approximately 80% of the total measured plasma radioiodine up to 24 h after an administered 125I – dose (Mahle et al., 2002). This
apparent discrepancy may be explained by the slow incorporation of administered or ingested iodide into hormones over time. Endogenous serum iodine
data primarily reflect hormone-incorporated iodine, since the system is at
steady state. This normal iodine turnover is well established in the animal when
the radioiodide is introduced. However, the kinetics reflected in the radiolabeled iodide time course is primarily due to binding of the free anion to plasma
proteins, uptake of the anion into various tissues, and urinary clearance.
Hormone incorporation would have little effect on these radioiodide kinetics,
due to the long time-frame required to incorporate the radioiodide into hormones in the thyroid and the slow secretion of these newly produced radiolabeled hormones into the serum. The model is able to reconcile these data by
including an incorporated iodine compartment in the plasma, into which the
hormone-incorporated iodine enters as it is secreted from the thyroid. A
generic first order rate (ClDeiodc i) is then used to describe the overall deiodination accomplished in the various tissues, allowing the inorganic iodide to
re-enter the free plasma compartment.
Some description of plasma binding was required for both anions in order to
adequately reproduce the available data. The inclusion of binding to plasma
proteins is especially important in the case of perchlorate. In fact, at low serum
concentrations (ⱕ100 ␮g/l), approximately 99% of the anion is bound to
plasma proteins and at higher concentrations (ⱖ500 ␮g/l), 50% is bound (J. W.
419
Fisher, personal communication). Binding of perchlorate to plasma proteins
has also been measured in both human and bovine serum (Carr, 1952; Scatchard and Black, 1949). Iodine also binds to plasma proteins, but to a lesser
extent than ClO 4 ⫺. Therefore, the model includes a description for the binding
of I – and ClO 4 ⫺ to plasma proteins. Competition of the two anions for plasma
binding sites was also included in the model.
In addition to the reported presence of NIS in the mammary gland (Spitzweg
et al., 1998), studies of perchlorate-induced inhibition of iodide uptake in milk
and mammary tissue support the conclusion that a transport mechanism similar
to that of the thyroid exists in the mammary gland (Brown-Grant, 1957;
Grosvenor, 1963; Potter et al., 1959). Furthermore, hormones produced during
lactation, such as prolactin, regulate the mammary gland NIS activity (Tazebay
et al., 2000). Shennan and Peaker (2000) also found evidence of a second anion
transport mechanism in the secretory cells of the mammary gland, suggesting
that this transporter is also able to move iodide and perchlorate against a
concentration gradient. This second anion channel is represented in the model
as active uptake into the milk compartment.
The kidney and liver were separately defined within the structure of the
model in order to describe the rapid urinary clearance of the anions and to
allow for future elaboration of the model that would address hormone metabolism in the liver. A fat compartment was also included to account for the
possible effect of changing fat volume on the kinetics due to the hydrophilic
nature of both anions. Since kidney, liver, and fat do not maintain tissue:
plasma ratios greater than one for either anion, these tissues were described as
single, flow-limited compartments and do not contain terms for active uptake.
Effective partitioning into these compartments is thought to result from the
electrochemical gradient that moves ClO 4 ⫺ from serum to tissue (Chow and
Woodbury, 1970).
The basic structure of the neonatal model (Fig. 1A) is similar to that of the
lactating rat, excluding the mammary gland. In order to simplify the model, all
pups from a single litter were combined together within the model structure.
Neonatal dose is described as a first order transfer rate between the maternal
milk and pup GI contents. The anions are then recirculated to the mother
through the pup urine based on the work of Samel and Caputa (1965), showing
that lactating dams ingest approximately 60% of the neonate’s iodine dose
while grooming their pups.
Perchlorate-induced inhibition of iodide uptake was included in the maternal
and neonatal thyroid follicle and colloid, GI contents and skin, as well as the
maternal mammary gland and milk. Literature sources have reported inhibition
of iodide uptake into gastric juice of the male rat (Halmi and Stuelke, 1959)
and the milk of the lactating rat (Brown-Grant, 1957; Grosvenor, 1963; Potter
et al., 1959). Studies in our laboratory have also shown consistent evidence of
significant inhibition of iodide uptake in neonatal GI and skin, and slight
inhibition in the maternal skin and mammary gland (Mahle et al., 2002).
Dosing Procedures
In order to simulate the daily dosing regimen of the perchlorate drinking
water experiment, a pulse function in ACSL was used to introduce drinking
water to the GI contents of the lactating dam at a constant rate for 12 h per day
(1800 to 0600 h). The neonate was dosed continuously throughout the day
from the maternal milk. Both the pup milk dose and the oral bolus dose were
introduced into the GI contents of the neonate utilizing pulse functions. Tail
vein injections were simulated by introducing the anions into the iv serum
compartment. Dosing for the dietary iodine studies (Stolc et al., 1973a,b) was
based on the iodine content of the feed and supplemented water, as well as
published water, milk, and dietary intake data (Stolc et al., 1966) in both the
maternal and neonatal rat throughout the postnatal time period, assuming a
constant (24 h/day) intake for both dam and neonate.
Model Parameters
Model equations are described in the Appendix. Whenever possible, physiological and kinetic parameters were obtained from literature or experiments.
Allometric scaling was generally employed to account for differences in
420
CLEWELL ET AL.
TABLE 1
Physiological Parameters
Lactation
Parameters
Tissue volumes
Body weight BW (kg)
Slowly perfused VSc (%BW)
Richly perfused VRc (%BW)
Fat VFc (%BW)
Kidney VKc (%BW)
Liver VLc (%BW)
Stomach tissue VGc (%BW)
Gastric juice VGJc (%BW)
Stomach blood VGBc (%VG)
Skin tissue VSkc (%BW)
Skin blood VSkBc (%VSkc)
Thyroid total VTc (%BW)
Thyroid follicle VTFc (%Vttot)
Thyroid colloid VTLc (%VTtot)
Thyroid blood VTBc (%VTtot)
Plasma VPlasc (%BW)
Red blood cells VRBCc (%BW)
Mammary tissue VMc (%BW)
Mammary blood VMBc (%VM)
Milk VMk (l)
Blood flows
Cardiac output QCc (l/h/kg)
Slowly perfused QSc (%QC)
Richly perfused QRc (%QC)
Fat QFc (%QC)
Kidney QKc (%QC)
Liver QLc (%QC)
GI QGc (%QC)
Skin QSkc (%QC)
Thyroid QTc (%QC)
Mammary QMc (%QC)
Dam
Neonate
Source
0.277–0.310
37.07–40.42
5.35
12.45–6.9
1.7
3.4
3.9
7.2
2.9
19.0
2.0
0.0105
45.89
45
9.1
4.7
2.74
4.4–6.6
18.1
0.002
0.0075–0.1985
53.92–49.31
5.36
0.0–4.61
1.7
3.4
3.9
7.2
2.9
19.0
2.0
0.0125
61.4–37.2
18.3–32.5
20.3–30.3
4.7
2.74
—
—
—
Yu et al., 2001
Brown et al., 1997
Brown et al., 1997
Naismith et al., 1982
Brown et al., 1997
Brown et al., 1997
Merrill et al., 2003
Yu et al., 2002
Altman and Dittmer, 1971
Brown et al., 1997
Brown et al., 1997
Florsheim et al., 1966; Malendowicz and Bednarek, 1986
Conde et al., 1991; Malendowicz and Bednarek, 1986
Conde et al., 1991; Malendowicz and Bednarek, 1986
Conde et al., 1991; Malendowicz and Bednarek, 1986
Altman and Dittmer, 1971; Brown et al., 1997
Altman and Dittmer, 1971; Brown et al., 1997
Knight et al., 1984
Assume same % as thyroid blood
Fisher et al., 1990
14.0–21.0
7.9–1.9
40.8
7.0
14.0
18.0
1.61
0.058
1.6
9.0–15.0
14.0
16.9
40.8
7.0
14.0
18.0
1.61
0.058
1.6
—
parameters due to variations in body weight of male, female, and neonatal rats.
Tissue volumes were scaled linearly by body weight (BW). Blood flows,
maximum velocities, permeability area cross products (PA), and clearance
values were scaled by BW 0.75. Pup values were scaled in a similar manner to
the maternal parameters. Physiological and chemical-specific parameters were
scaled first by the body weight of an individual pup, as described above, and
were then multiplied by the total number of neonates to represent the value for
the entire the litter.
Physiological parameters. The physiological description of maternal and
neonatal rats during lactation is based on the work of Fisher et al. (1990),
measurements from our laboratory and published physiological data. Due to
the nonuniform changes in tissue volume and body weight during lactation, it
was necessary to include gender and life stage-specific physiological descriptions whenever possible. Parameters that were not available specifically for the
lactating female or neonate were described by adjusting male rat values by
body weight. Final values for the physiological parameters and sources from
which they were obtained are listed in Table 1.
Lactation-specific changes in tissue volumes and suckling rates were included in the model using ACSL TABLE functions, which employ linear
interpolation between available data points. Maternal body weight was assumed to increase by 12% between PND 1 and 10, based on the daily
measurements of dams in the perchlorate drinking water study described
Brown et al., 1997; Hanwell and Linzell, 1973
Brown et al., 1997
Brown et al., 1997
Brown et al., 1997
Brown et al., 1997
Brown et al., 1997
Brown et al., 1997
Brown et al., 1997
Brown et al., 1997
Hanwell and Linzell, 1973
previously. Since there was no significant difference in the average daily body
weights between the five dose groups, the average body weight from all doses
were used. The relative volume of the mammary tissue increased from 4.4% on
PND 2 to 5.6, 6.3, and 6.6% of the maternal body weight on PND 7, 14, and
21, respectively (Knight et al., 1984). Maternal body fat increased from 12.4
to 15.2% of the body weight between parturition and PND 2, with a subsequent
decrease to 6.9% of the body weight from PND 2 to 16 (Naismith et al., 1982).
Values for body fat content on PND 2 and 16 were taken from the measured
values of Naismith et al. (1982). Maternal body fat at parturition was calculated from the previously developed PBPK model for the pregnant rat (Clewell
et al., 2003). Thus, the relative volume of the maternal body fat in the model
increases slightly between PND 1 and 2 and then decreases after PND 2. The
rate of milk production was assumed to be equal to the suckling rate described
below.
As in the maternal tissues, TABLE functions were used to interpolate
between reported data points for the changing body weight, suckling rate, and
relative tissue volumes in the neonate. Growth of the neonate is directly
dependent on the ingestion of milk. Stolc et al. (1966) measured both pup body
weight and the milk ingestion of suckling rats from birth through weaning.
Although the author used a different strain of rats than was used in our studies,
the pup body weights were nearly identical between the two studies. Thus, the
more comprehensive, published data set of Stolc et al. (1966) was used for
PBPK ClO 4 ⫺ MODEL FOR RAT LACTATION
these physiological parameters. Values for neonatal body fat were based on the
data of Naismith et al. (1982), showing a rapid increase from 2.7 to 11% BW
between PND 2 and 16 and a subsequent decrease to the adult value of 4.61%
(Brown et al., 1997).
Increase in neonatal thyroid volume was based on the work of Florsheim et
al. (1966), who reported relative thyroid volumes of 0.013, 0.015, 0.012,
0.014, 0.013, 0.013, and 0.013% body weight for neonates on PND 1 through
5, 7, and 11, respectively. The model also describes changing thyroid stroma,
follicle, and colloid fractions over time based on the work of Conde et al.
(1991), who measured the fractional volumes on postnatal days 0, 5, 10, 15, 20,
25, 30, 60, and 120. Relative tissue volumes of the skin, GI tract, liver, and
kidney were modeled based on measured body and tissue weights on PND 1,
5, 10, 20, 30, and 64 (Palou et al., 1983). Relative skin volume increased from
19.3 to 20.8% BW from PND 1 to 20 and then decreased to 19% BW by PND
30. Similar trends were also seen in the GI, kidney, and liver, with increasing
volume (with respect to body weight) peaking at PND 30, 20, and 30,
respectively.
All maternal blood flows that were not directly affected by the changes
induced by lactation were scaled allometrically from the adult male rat parameters. TABLE functions were used to describe the changing in cardiac output
and fractional blood flow to the mammary tissue throughout lactation, according to the data of Hanwell and Linzell (1973) and the neonatal cardiac output,
hematocrit, and regional blood flows, based on the data of Rakusan and
Marcinek (1973). Among other tissues, Rakusan and Marcinek (1973) measured fractional blood flows to the kidney, liver, skin, stomach, and large and
small intestines in 1, 30, 60, and 140 day-old rats. Relative blood flow to the
neonatal kidney, liver, and total GI are modeled as increasing from 3.6, 4.5,
and 4.6 to 15.5, 5.2, and 6.8% cardiac output, respectively, in the first 60 days.
Blood flow to the skin remains relatively constant after birth, at approximately
11% of the cardiac output.
Chemical-specific parameters. Chemical-specific parameters (Table 2)
for perchlorate and iodide in tissues other than the mammary gland were kept
as similar as possible to those used in the PBPK models for the male and
pregnant rat (Clewell et al., 2003; Merrill et al., 2003) in order to facilitate
comparison of the models and extrapolation between life-stages. As in the
previous models, binding of I – to NIS was given a K m of 4.0 ⫻ 10 6 ng/l based
on the work of Gluzman and Niepomniszcze (1983) in human thyroid slices.
This value for the follicular K m (KmTF i) remained constant across species
(Gluzman and Niepomniszcze, 1983) and tissues (Wolff, 1998) and was
therefore applied to all compartments in the model with NIS. The second
transporter located at the apical membrane in the thyroid was studied by
Golstein et al. (1992), who measured a K m of approximately 4.0 ⫻ 10 9 ng/l for
iodide (KmTL i) in bovine thyroid. In the model, a somewhat lower value than
that measured by Golstein et al. of 1.0 ⫻ 10 9 was used for KmTL i, based on
the ability of the model to fit the later (⬎8 h) time points. The K m for the
second active transport mechanism in the mammary gland (KmMk), for milk
uptake, was set by fitting the model simulation to available mammary gland
and milk data.
The K m value for ClO 4 ⫺ transport by NIS was given a value of 1.5 ⫻ 10 5
ng/l for all relevant compartments. This value is based on the assumption that
perchlorate acts as a competitive inhibitor of iodide uptake and is, in fact,
transferred into the tissues via NIS (Clewell and Gearhart, 2002b). Therefore,
the K m value for perchlorate transport by NIS would be equal to its K i value.
Kosugi et al. (1996) measured the K i for ClO 4 ⫺ at 1.5 ⫻ 10 5 ng/l. This value
was adjusted slightly to obtain the best fit of thyroid perchlorate to the drinking
water data, resulting in a K m of 2.0 ⫻ 10 5ng/l. This value is further supported
by various literature sources suggesting that ClO 4 ⫺ actually has as much as an
order of magnitude greater affinity for NIS than I – itself (Chow et al., 1969;
Halmi and Stuelke, 1959; Harden et al., 1968; Lazarus et al., 1974). Likewise,
the K m values for perchlorate transport by the second anion channels in the
thyroid and mammary gland were also nearly a factor of 10 less than that of
iodide, resulting in values of 1.0 ⫻ 10 8 and 1.0 ⫻ 10 6 ng/l for KmTL p and
KmMk p, respectively.
The values for V max vary significantly across species and tissues with NIS
421
(Gluzman and Niepomniszcze, 1983; Wolff, 1998) and were, therefore, determined by fitting the model simulations to available data in the various tissues
of PND 5 and 10 rats. In the perchlorate drinking water study, the nonlinearity
of tissue ClO 4 ⫺ concentrations across doses in compartments with NIS suggests that the symporter is saturated between the 1.0 and 10.0 mg/kg-day doses.
Thus at doses below saturation (ⱕ1.0 mg ClO 4 ⫺/kg-day), the active transport
via NIS would drive tissue concentrations and were therefore used to set V max
values. For iodide, kinetic data were taken at doses well below the saturation
of NIS. Thus, the time course data from the kinetic studies were used to
determine values for V max in tissues with active uptake.
Partitioning of ClO 4 ⫺ and I – into tissues results from the electrochemical
potential present across tissue membranes (Chow and Woodbury, 1970).
Theoretical effective partition coefficients were calculated from measured
electrical potentials presented by Chow and Woodbury (1970) using the
equations given in Kotyk and Janacek (1977). Calculations are described in
detail in the male rat perchlorate model (Merrill et al., 2003). Ranges for the
partition coefficients corresponding to the stroma:follicle and follicle:lumen
membrane diffusion were estimated to be 0.11 to 0.15 and 6.48 to 8.74,
respectively. Based on the fit of the model simulation to the data and the
calculated values above, values of 0.15 and 7.0 were used for PTF i and PTL i,
respectively.
As mentioned previously, the perchlorate drinking water data indicate that
NIS transport is saturated between the 1.0 and 10.0 mg ClO 4 ⫺/kg-day doses.
Therefore, at 10.0 mg/kg-day, ClO 4 ⫺ uptake into the various tissues would be
predominantly determined by the passive diffusion parameters. Thus, parameters describing partitioning of ClO 4 ⫺ into the tissues were obtained by fitting
the model simulation to the highest dose group data from the drinking water
study. In the cases where data were not available in the lactating or neonatal
rat, such as the muscle (slowly perfused), liver (richly perfused), kidney, and
red blood cells, values were obtained from those used in the adult male rat
model (Merrill et al., 2003). The partition coefficient for perchlorate in fat was
measured in the laying hen (Pena et al., 1976). Other tissues in the hen, such
as the muscle and kidney, were found to have similar partition coefficients to
those of the rat.
Iodide partition coefficients and PA values were calculated from the tissue:
blood ratios measured during the clearance phase of data for the tissue of
interest either from literature or experimental data in the rat. The partitioning
parameters for the muscle (slowly perfused), liver (richly perfused), kidney,
and red blood cells were given the same values measured in the male rat
(Merrill et al., 2003) and the value for partitioning of iodide into the fat was
given the same value as ClO 4 ⫺.
Parameters for plasma binding were determined by fitting the model to time
course data in the case of iodide and the 0.01 and 0.1 mg/kg-day drinking water
data in the case of ClO 4 ⫺, due to the fact that binding was most prevalent at the
lower doses. Urinary clearance of ClO 4 ⫺ was determined from fitting the
serum at the 10.0 mg/kg-day dose group, where binding had little effect on
serum concentrations. First-order clearances for incorporation of iodide into
thyroid hormones and hormone secretion were determined by the fit of the
model to the incorporated and free thyroid iodide time course data. Parameters
for binding of inorganic iodide to plasma proteins were determined by the fit
of the model simulation to initial portion of the serum radioiodine data. Later
time points were assumed to be more affected by hormone secretion and deiodination rates, as sufficient time had passed to allow for incorporation of the
administered radioiodide into hormones. Urinary iodide clearance was determined
from the fit of the model to serum inorganic iodide time course data.
Upregulation of thyroid NIS activity. At the time of data collection in the
drinking water study, rats had been exposed to ClO 4 ⫺ throughout gestation and
up to the day of sacrifice. At this point, upregulation of the thyroid activity is
evidenced by decreased T 4 and elevated TSH levels in the serum at all doses,
as well as a lack of noticeable thyroid iodide uptake inhibition (Yu et al.,
2001). Since increased TSH upregulates thyroid iodide uptake by increasing
the number and activity of NIS (Wolff, 1998), the value for VmaxcTF i, which
corresponds to the maximum capacity of active transport at the basolateral
membrane, was increased to fit the measured radioiodide concentrations in the
422
CLEWELL ET AL.
TABLE 2
Chemical-Specific Parameters
Perchlorate
Parameters
Partition coefficients (unitless)
Slowly perfused/plasma PS
Rapidly perfused/plasma PR
Fat/plasma PF
Kidney/plasma PK
Liver/plasma PL
Gastric tissue/gastric blood PG
Gastric juice/gastric tissue PGJ
Skin tissue/skin blood PSk
Thyroid tissue/thyroid blood PTF
Thyroid lumen/thyroid tissue PTL
Red blood cells/plasma PRBC
Mammary tissue/mammary blood PM
Mammary/milk PMk
Max capacity, Vmaxc (ng/h/kg)
Thyroid follicle VmaxcTF
Thyroid colloid VmaxcTL
Skin VmaxcS
GI VmaxcG
Mammary VmaxcM
Milk VmaxcMk
Affinity constants, Km (ng/l)
Thyroid follicle KmTF
Thyroid lumen KmTL
Skin KmS
GI KmG
Mammary KmM
Milk KmMk
Permeability area cross products (l/h-kg)
Gastric blood to gastric tissue PAGc
Gastric tissue to gastric juice PAGJc
Thyroid blood to thyroid tissue PATFc
Thyroid tissue to thyroid lumen PATLc
Skin blood to skin tissue PASkc
Mammary blood to mammary tissue PAMc
Mammary tissue/milk PAMkc
Plasma to red blood cells PARBCc
Clearance values (l/h-kg)
Urinary excretion CLUc
Fraction of pup urine ingested by dam
Hormone productions rate ClProdc_i
Hormone secretion rate ClSecrc_i
Deiodination
Binding constants
VmaxcB
KmB
Kunbc
Dam
0.31
0.5
0.05
0.99
0.56
1.80
2.30
1.15
0.13
7.0
0.73
0.66
2.39
Iodide
Pup
Dam
Pup
0.31
0.5
0.05
0.99
0.56
3.21
5.64
1.15
0.13
7.0
0.73
—
—
0.21
0.4
0.05
1.09
0.44
1.00
1.00
0.70
0.15
7.0
1.00
0.80
1.00
0.21
0.4
0.05
1.09
0.44
1.20
1.00
1.00
0.15
7.0
1.00
—
—
1.5 ⫻ 10 3
1.0 ⫻ 10 4
8.0 ⫻ 10 5
1.0 ⫻ 10 6
2.0 ⫻ 10 4
2.0 ⫻ 10 4
1.50 ⫻ 10 3
1.0 ⫻ 10 4
8.0 ⫻ 10 5
1.0 ⫻ 10 6
—
—
5.0 ⫻ 10 4
6.0 ⫻ 10 7
4.0 ⫻ 10 5
2.0 ⫻ 10 6
8.0 ⫻ 10 5
4.0 ⫻ 10 5
1.3 ⫻ 10 4
6.0 ⫻ 10 7
2.5 ⫻ 10 5
2.0 ⫻ 10 6
—
—
1.5 ⫻ 10 5
1.0 ⫻ 10 8
1.5 ⫻ 10 5
1.5 ⫻ 10 5
1.5 ⫻ 10 5
1.0 ⫻ 10 6
1.5 ⫻ 10 5
1.0 ⫻ 10 8
1.5 ⫻ 10 5
—
—
—
4.0 ⫻ 10 6
1.0 ⫻ 10 9
4.0 ⫻ 10 6
4.0 ⫻ 10 6
4.0 ⫻ 10 6
1.0 ⫻ 10 7
4.0 ⫻ 10 6
1.0 ⫻ 10 9
4.0 ⫻ 10 6
—
—
—
1.00
1.00
4.0 ⫻ 10 –5
0.01
0.50
0.01
0.10
1.00
1.00
1.00
4.0 ⫻ 10 –5
0.01
1.00
—
—
1.00
0.80
0.60
1.0 ⫻ 10 –4
1.0 ⫻ 10 –4
0.20
0.02
0.02
1.00
0.04
0.09
1.0 ⫻ 10 –4
1.0 ⫻ 10 –4
0.02
—
—
1.00
0.07
0.80
—
—
—
0.0075
—
—
—
0.06
0.80
0.1
7.0 ⫻ 10 –7
0.02
0.06
1.0 ⫻ 10 –6
0.025
9.0 ⫻ 10 3
1.0 ⫻ 10 4
0.034
2.0 ⫻ 10 3
1.0 ⫻ 10 4
0.01
1.5 ⫻ 10 3
1.0 ⫻ 10 5
0.09
500
1.0 ⫻ 10 5
0.05
upregulated thyroids for each dose. The resulting values for VmaxcTF i were
then plotted versus the corresponding concentrations of serum free ClO 4 ⫺ and
the data were fitted with an M-M equation. This equation then was used in the
model to describe the induction of NIS upregulation with dose, in a similar
manner to the description used by Andersen et al. (1984) to describe enzyme
induction.
Upregulation of thyroidal NIS also affects thyroid ClO 4 ⫺ uptake, and hence
the measured thyroid ClO 4 ⫺ concentrations in the drinking water study, as both
0.012
ClO 4 ⫺ and I – are transported by the same symporter (Wolff, 1964, 1998). Thus,
increased thyroid ClO 4 ⫺ uptake was modeled in the same manner as I –,
increasing the value for VmaxcTF p with dose and applying the resulting M-M
fit to the model.
Dietary iodine model. The dietary iodine model is identical to that of the
radioiodine model. Dosing is accomplished as a constant intake of iodine
through water and diet. All chemical-specific parameters are assumed to be the
PBPK ClO 4 ⫺ MODEL FOR RAT LACTATION
same as those determined from the radioiodide kinetics. The radioiodide,
endogenous iodine and perchlorate models operate independently in tissues
with passive diffusion, and are linked through competitive uptake in tissues
with NIS (e.g., thyroid follicle). Thus, in tissues governed by passive diffusion,
tissue:blood ratios are identical for the radiolabeled and dietary iodine models.
The interaction of the three models through competitive inhibition at NIS
allows us to explore the effect of varying dietary intake on both radiolabeled
iodine kinetics and perchlorate-induced inhibition of radioiodide uptake in the
thyroid.
Sensitivity analysis of chemical-specific parameters. A sensitivity analysis was run after finalizing the model parameters as to examine the relative
influence of each of the chemical-specific parameters on model predictions.
The model was run to determine the change in the average serum ClO 4 ⫺
concentration (AUC: area under the curve) and total thyroid iodide uptake at
8 h postdosing, resulting from a 1% change in the value of each kinetic
parameter. In an effort to determine the effect of NIS saturation on relative
parameter importance, the sensitivity analysis was performed at two ClO 4 ⫺
doses, presumably representing unsaturated and saturated symporter states (0.1
and 10.0 mg-kg-day, respectively). Since the iodide doses used in this model
are not expected to saturate the NIS, thyroid iodide sensitivity analysis was run
only at the dose used in the kinetic experiments (2.1 ng/kg 125I –). The following
equation shows the calculation of the sensitivity coefficient for each parameter.
423
behavior of iodide data, where increasing PA values toward 1.0
l/h-kg generally increased the rate at which uptake and clearance in a particular tissue occurred, and decreasing PA slowed
uptake and clearance. Model simulations of radioiodide kinetics in maternal and neonatal tissues versus the data obtained
from dosing the dams are shown as the control group in the
inhibition study (Fig. 3). The fit of the model to iodide levels
in maternal and neonatal tissues from the direct oral dosing of
PND 10 pups are shown in Figure 4. The model was able to
reproduce data in both maternal and neonatal tissues, whether
exposure occurred via maternal iv or oral bolus to the pup.
Thus, the model is able to describe both maternal to neonatal
and neonatal to maternal iodide transfer, and is also able to
reproduce data across exposure routes.
RESULTS
Model validation. Once model parameters were established as described above, the robustness of the model was
tested against a variety of data sets taken across different
laboratories, rat strains, exposure routes, and time points in
lactation. Several published kinetic studies using various isotopes of iodide were used to test the model description of
iodide kinetics in the dam and neonate (see below). Accuracy
and usefulness of the model perchlorate and iodide descriptions
were further validated against studies of perchlorate-induced
inhibition of iodide uptake in the maternal thyroid, mammary
gland, milk, and neonatal tissues based on the description of
competitive binding to NIS.
The ClO 4 ⫺ data from the drinking water study were used to
determine kinetic parameters for ClO 4 ⫺ in the lactating and
neonatal rat. Upregulation of NIS transport of ClO 4 ⫺ into the
thyroid was accounted for as described in the Methods section.
Figure 2 shows the model simulations for ClO 4 ⫺ concentrations in the maternal and neonatal serum, maternal thyroid, GI
contents, mammary gland, and milk, versus measured data
from the drinking water study on PND 5 and 10 at 0.01, 0.1,
1.0, and 10.0 mg ClO 4 ⫺/kg-day. The upregulated values for
Vmaxc_TFp were used in the simulation of the thyroid as
described in the Methods section. In these and subsequent
plots, solid lines indicate the model prediction and cross-bars
indicate the mean ⫾ SD of measured data.
Neonatal iodide kinetic parameters were determined by the
fit of the model to the data obtained from directly dosing the
pup, while maternal parameters were primarily determined
from the data obtained by dosing the dam via iv. Transfer from
the neonate to the dam was established by fitting the maternal
kinetic parameters first and then utilizing maternal data from
the pup dosing study to determine the magnitude of iodide
transfer to the maternal stomach via pup urine. In the same
way, milk transfer was parameterized by first fitting the neonatal parameters from the pup dosing study and then utilizing
the pup data from the maternal dosing kinetic study to estimate
pup exposure via milk. PA values were adjusted to describe the
Radioiodide kinetics on PND 10. Validation of PND 10
iodide kinetics was performed with the data of Iino and Greer
(1961), Samel and Caputa (1965), Vigouroux (1976), and
Vigouroux and Rostaqui (1980). In order to simplify comparison of the different data sets, which were originally performed
at slightly different dose levels, the data of each study were
normalized to a dose of 1.0 ng. The model simulation was then
run versus the combined data sets (Fig. 5). Figures 5A and 5B
show the maternal and neonatal thyroid radioiodide levels on
PND 10 following an acute 131I – dose to the dam. The model is
able to predict the maternal thyroid iodide, but underpredicts
pup thyroid iodide levels at the 24 h time point. However, the
model prediction is within a factor of two of the measured data.
Figures 5C and 5D show the model-predicted maternal and
neonatal thyroid iodide levels after an ip dose to the pup. The
model simulation is able to describe both maternal and neonatal thyroid uptake, again within a factor of two.
The data of Samel and Caputa (1965) also allowed validation of the model parameters for urinary output in the pup.
Difficulty in separating maternal and pup urine precluded the
collection of these data in our own studies. Therefore, urinary
clearance values in the model were determined by the fit of the
serum to the time course data. Using the previously determined
kinetic parameters, the model-predicted urinary iodide, 4 h
after an iv dose of 131I – in the PND 10 rat, was 14% of the pup
dose, which is close to the range of values (0.61 to 10.9%)
given by Samel and Caputa (1965).
Sensitivity Coefficient ⫽
共A ⫺ B兲/B
(C ⫺ D)/D
where A is the serum AUC with 1% increased parameter value, B is the serum
AUC at the starting parameter value, C is the parameter value after 1%
increase, and D is the original parameter value.
Model Parameterization
424
CLEWELL ET AL.
FIG. 2. Perchlorate concentration in
maternal (A) serum (Clewell et al.,
2001), (B) thyroid (upregulated) (Clewell et al., 2001), (C) GI contents, (D)
mammary gland, (E) milk (Clewell and
Gearhart, 2002a), and (F) male neonatal
serum (Clewell and Gearhart, 2002a) at
the 0.01, 0.1, 1.0, and 10.0 mg/kg-day
doses on PND 5 and 10. Solid lines indicate model prediction. Cross-bars indicate mean ⫾ SD of the measured data.
Radioiodide kinetics on PND 5. In order to determine
whether the model would provide reasonable predictions of
iodide and perchlorate kinetics in younger pups (⬍PND 10),
the model was tested against data obtained in our laboratory
after a single iv injection of 125I – on PND 5 of the ClO 4 ⫺ drinking
water study. Since the control group did not receive perchlorate
during the study, tissue 125I – data from these animals can be
used to confirm the model’s ability to predict kinetics in PND
5 rats. Figure 6 shows that the model-predicted radioiodide
concentrations in the maternal serum, thyroid and mammary
gland and neonatal serum are in good agreement with the
available data on PND 5.
Upregulation of thyroid NIS activity was modeled against
the thyroid iodide levels measured after 23 days of exposure to
perchlorate in drinking water at doses of 0.01, 0.1, 1.0, and
10.0 mg ClO 4 ⫺/kg-day as was described in the Methods sec-
PBPK ClO 4 ⫺ MODEL FOR RAT LACTATION
425
FIG. 3. Concentration of maternal
(A) inorganic radioiodide in serum, (B)
plasma bound radioiodine, (C) thyroidal
inorganic radioiodide and incorporated
radioiodine, (D) mammary gland, and
neonatal (E) serum after an iv dose to the
dam of 2.10 ng/kg 125I – on PND 10.
tion. Using this equation for the upregulation of the follicular
Vmaxc (VmaxcTF i), it was possible to describe the increase in
iodide uptake based on the perchlorate dose in chronic exposure scenarios. Neither the measured data nor the model
showed any inhibition in iodide concentrations in the maternal
thyroid 2 h postdosing with 125I – after 18 days of exposure to
0.01, 0.1, 1.0, and 10.0 mg/kg ClO 4 ⫺ in drinking water. Thus,
the model was able to describe the upregulation of thyroid NIS
activity resulting from subchronic perchlorate exposures.
Radioiodide kinetics in late lactation. The model’s ability
to simulate iodide kinetics at later time points in lactation
426
CLEWELL ET AL.
FIG. 4. Concentration of neonatal
(A) plasma bound radioiodine and
plasma inorganic radioiodide, (B) thyroidal incorporated radioiodine and inorganic radioiodide, (C) GI contents (filled
circles) and skin (open squares) radioiodide, and (D) maternal total serum and
thyroid radioiodine after an oral gavage
of 1.0 ng/kg 125I – to the pup on PND 10.
(⬎PND 10) was tested against the normalized data of several
literature studies. Figure 7 shows the model-predicted radioiodide milk:plasma ratio versus the data of Brown-Grant (1957),
Grosvenor (1963), and Potter et al. (1959) collected on PND
14, 17–20, and 18, respectively. Although the simulation
shown in Figure 7 was run on PND 14, there is no noticeable
change in the model-predicted milk:plasma ratio when run at
different days in lactation. Despite the changing kinetics (body
composition, suckling rate, etc.), the model prediction of relative iodide concentration in the milk remains constant. Although the amount of milk provided to the infant may change
during the course of lactation, the concentration of iodide does
not. This assumption is supported by the available data, which
do not show any increasing or decreasing trend in milk iodide
concentrations. Dietary iodine studies by Stolc et al. (1966;
1973a,b) also showed a relatively unchanging milk iodine
concentration through the different stages of lactation. The
model predictions are in reasonable agreement with the trend
suggested by the total composite of the different data sets.
The maternal urinary iodide was tested against the data of
Grosvenor (1960). For the reasons mentioned previously, urine
was not collected in our own studies. Thus, model parameters
for maternal urinary clearance (ClUc i) were determined by
fitting the model simulation to serum time course data, while
maintaining fits to data in the thyroid, mammary gland, and
pup. Using these previously set parameters, the model predicts
that 40.8% of the 131I – dose will be excreted within 8 h
post- 131I – dosing, which is within the range of 36.7 to 42.1%
reported in Grosvenor’s 1960 study.
Perchlorate-induced inhibition of iodide uptake. The ability of the model to predict inhibition of iodide uptake into the
thyroid, milk, and other tissues is not only important in calculating risk to the dam and neonate, but is also indicative of the
model’s ability to accurately describe both perchlorate and
iodide kinetics. Thus, the available data for perchlorate-induced inhibition of iodide kinetics in lactation was used as the
final validation of the current model structure. Using the conditions for the inhibition time course study described in the
Methods section, the model simulation was run to predict the
effect of the administration of 1.0 mg ClO 4 ⫺/kg on the kinetic
behavior of an iv dose of radioiodide (given 2 h post-ClO 4 ⫺
dosing). Figure 8 shows that the model accurately simulates
inhibition of iodide uptake in the maternal thyroid and mam-
PBPK ClO 4 ⫺ MODEL FOR RAT LACTATION
427
FIG. 5. Amount of radioiodide in
(A) maternal and (B) neonatal thyroid
after iv dose to dam and in (C) maternal
and (D) neonatal serum after iv dose to
pup on PND 10 versus the normalized
data (1.0 ng 131I –) of (open circles) Iino
and Greer (1961), (filled squares) Samel
and Caputa (1965), (filled triangles) Vigouroux (1976), and (filled circles) Vigouroux and Rostaqui (1980).
mary gland. The simulations of the iodide inhibition kinetics in
the mammary gland also suggest that the model is able to
predict the affect of perchlorate exposure on the availability of
iodide to the neonate. Although NIS inhibition would occur in
both maternal GI and skin, neither the data nor the model
showed significant difference between the control and ClO 4 ⫺
dosed animals, suggesting that other factors (i.e., diffusion,
partitioning) are offsetting the effects of symporter inhibition.
The model-predicted inhibition of both milk and thyroid
iodide was validated against the data of Potter et al. (1959).
Potter and coauthors measured the amount of radioiodide ( 131I –)
taken up into the thyroid gland and the combined mammary
gland and expressed milk 24 h after dosing with iodide in PND
18 rats. The total effect on iodide uptake was measured after
two ClO 4 ⫺ doses given 1 h prior to and 30 min after the
radioiodide dose. At these large doses of ClO 4 ⫺, thyroid iodide
uptake is essentially blocked (approximately 99% inhibition).
Therefore, it is likely that the NIS transport of iodide into the
mammary gland is also completely inhibited. However, unlike
the thyroid, the milk still showed significant amounts of iodide
(approximately 10% of the control value at 24 h). It is possible
that the second mammary transport mechanism is responsible
for this difference in tissue response to ClO 4 ⫺ exposure, because it depletes iodine content in the mammary gland to the
extent that passive diffusion between the gland and the blood
becomes significant. In contrast, passive diffusion of iodine
into the thyroid is restricted by the slow clearance via secretion
of hormones into the blood, as well as the lower permeability
and partitioning of the anions suggested by the model. The
ability of the model to predict the combined mammary gland
and milk control and ClO 4 ⫺ dosed data of Potter et al. (1959;
Fig. 9) supports the accuracy of the description of iodide
partitioning in the mammary gland and the second active
transporter. The model predicts the data remarkably well despite significant differences between this study and those used
for model development, such as different time points in lactation (PND 18 vs. 10) and a different dosing regimen.
Dietary iodine. In three separate experiments, Stolc et al.
(1966, 1973a,b) studied the distribution of endogenous iodine
in various tissues of the maternal and neonatal rat resulting
from a controlled intake of iodine through the diet and water.
Model-predictions of the maternal and neonatal tissue iodine
concentrations are shown in Figure 10 versus data collected at
428
CLEWELL ET AL.
FIG. 6. Radioiodide concentration in maternal serum, mammary gland,
thyroid, and neonatal serum versus the measured data after an iv dose of
33,000 ng/kg 131I– to the dam on PND 5.
water and feed concentrations of 60 ng I/g and 500 ng I/ml,
respectively (Stolc et al., 1973a), which corresponds to daily
doses of 4.8 mg I/kg-day. Of the three dosing levels presented
by Stolc and coauthors, this highest dose was chosen to validate the model prediction of normal iodine distribution, due to
the fact that it is within the range of normal dietary intake for
rats and it is closest to dietary intake expected for our experimental studies (800 ng I/mg food). The two lower dose groups
would be considered moderately deficient and deficient iodine
diets, resulting in changes in the H-P-T axis in order to affect
upregulation as is evidenced by the measured tissue iodine
concentrations. Despite a fivefold difference in water iodide
concentrations, the serum and thyroid concentrations remain
unchanged. Other tissues, including the skin and GI, do show
a dose-dependent change in tissue concentration. Thus, since
this model does not yet include the pharmacodynamic response
of the thyroid axis to dietary insufficiency, it is premature to
attempt to predict such data. Using kinetic parameters obtained
from acute data, the model is generally able to predict endogenous data within a factor of two of the measured data for
tissue concentrations ranging over more than four orders of
magnitude (Fig. 10).
While admittedly only a preliminary description, this endogenous iodine model could be exercised to assess the affect of
changing dietary intake on predicted acute radioiodide kinetics,
as well as predicted perchlorate-induced inhibition of radioiodide kinetics in the perinatal and adult rats. Since the radioiodide, endogenous iodine and perchlorate models operate inde-
pendently in tissues with passive diffusion, and are linked
through competitive uptake in tissues with NIS (e.g., thyroid
follicle), only tissues with active uptake are expected to show
any change in tissue concentrations with varying dietary intake. From this modeling exercise, it was determined that the
effects of changes in dietary iodine intake on acute radioiodide
kinetics are likely to be negligible. In fact, significant differences in predicted thyroid concentrations were not observed at
feed concentrations as high as 8.0 ppm (more than an order of
magnitude higher than standard laboratory diet). Indeed, the
first apparent change in predicted inhibition of thyroidal radioiodide uptake is seen at feed concentrations 100 times greater
than standard laboratory rat chow.
Sensitivity analysis. Sensitivity analysis performed at 0.1
and 10.0 mg ClO 4 ⫺/kg-day drinking water revealed a dosedependent difference in model sensitivity to several of the
chemical-specific parameters (Fig. 11). At 0.1 mg/kg-day, the
maternal serum is primarily dependent on serum binding,
showing less sensitivity to urinary clearance. All other parameters had calculated sensitivity coefficients less than 0.1. At the
10.0 mg/kg-day dose, binding parameters are no longer important determinants of predicted serum levels. Only the urinary
clearance remains significant, with a sensitivity coefficient of
– 0.87. Neonatal serum ClO 4 ⫺ levels are influenced by several
model parameters at the 0.1 mg/kg-day dose, including the
parameters defining passive diffusion and active transfer in the
FIG. 7. Radioiodide milk:plasma concentration after an iv dose to the dam
versus the combined literature data. The data points represent individual
measurements provided in (filled triangles) Brown-Grant (1957), (filled circles) Grosvenor (1963), and (filled squares) Potter et al. (1959) on PND 14, 18,
and 17–20, respectively.
PBPK ClO 4 ⫺ MODEL FOR RAT LACTATION
429
FIG. 8. Iodide concentration in (A)
maternal thyroid and (B) mammary
gland with and without 1.0 mg/kg ClO 4 ⫺
iv dose 2 h prior to an iv dose of 2.10
ng/kg 125I – to the dam on PND 10. The
top simulation (solid line) and data (open
squares) indicate the control group. The
lower simulation (dashed line) and data
(filled squares) indicate inhibition.
mammary gland, milk, and neonatal GI. However, similar to
dam, neonatal serum AUC shows the greatest sensitivity to
serum binding parameters at this lower dose. At the higher
dose (10.0 mg/kg-day), where active uptake into the mammary
gland and serum binding are likely saturated, partitioning into
mammary gland and milk and urinary clearance (both maternal
and neonatal) show the greatest influence on pup serum ClO 4 ⫺
levels. Results of the sensitivity analysis for thyroid iodide
uptake (not shown) were similar, in that the magnitude of all of
the parameter sensitivities were less than one, although model
predictions for this metric were sensitive to a much larger
number of input parameters. This result is not unexpected due
to the fact that the uptake prediction is for a specific point in
time after administration of the radioiodide, and the rate of
distribution into all tissues can effect the time-dependent result
[as compared to an average, or AUC (area under the curve),
measure, which reflects steady-state behavior]. Thus, the validation of the model with kinetic thyroid iodine uptake and
inhibition data provides a reasonable test of the model parameterization.
Calculation of Internal Dose Metrics
The model was used to calculate internal dose metrics corresponding to both acute and subchronic perchlorate exposure
in the lactating and neonatal rat. These internal measures of
dose include: AUC for ClO 4 ⫺ in the maternal and neonatal
serum, relative neonatal dose (% maternal dose) and inhibition
of thyroid iodide uptake after acute dosing. Table 3 shows the
predicted neonatal dose on PND 10 as % maternal dose and as
an amount adjusted for milk intake and pup body weight. The
model predicts a significant transfer of maternal ClO 4 ⫺ to the
FIG. 9. Radioiodide concentration in milk with and without ClO 4 ⫺
(Clewell et al., 2001). Perchlorate doses of 25 mg and 12.5 mg were given to
the dam 30 min before and 4 h after administration of 131I –, respectively. The
top simulation and data (filled triangles) indicate the control group. The lower
simulation and data (filled circles) indicate the inhibition group. Data points
represent milk samples from individual dams from Potter et al. (1959).
FIG. 10. Model predicted tissue iodine vs. measured data of Stolc et al.
(1973a) with a normal dietary intake (approximately 560 ng/day). Standard
deviations were given with the measured maternal data only.
430
CLEWELL ET AL.
FIG. 11. Calculated sensitivity coefficients for model parameters with respect to serum perchlorate AUC at drinking water doses of 0.1 and 10.0 mg/kgday.
neonate on PND 10 at low maternal doses. In fact, per kg body
weight, the PND 10 pup receives a greater dose than the dam
(0.07 vs. 0.01 mg/kg BW). Tables 4 and 5 show the dose metric
comparisons between the adult male, pregnant, fetal, lactating
and neonatal rats for serum ClO 4 ⫺ AUCs from drinking water
exposure, as well as thyroid iodide inhibition after acute iv
exposures in the adult male, GD 20 pregnant and fetal rats, and
the PND 10 lactating and neonatal rats. The internal dose
metrics in the lactating and neonatal rat were compared to
those of the male (Merrill et al., 2003), pregnant, and fetal rat
(Clewell et al., 2003) in order to provide insight on relative
exposure at different life stages. From Tables 4 and 5, it is
apparent that while the lactating rat shows the highest serum
ClO 4 ⫺ concentrations, the fetal rat actually shows the greatest
inhibition of thyroid iodide uptake.
DISCUSSION
The PBPK model is able to describe iodine kinetics across
doses, exposure routes, and time points during lactation for
both acute dosing and dietary iodine studies. The iodide model
was simplified by assuming that radiolabeled iodide could be
described as free iodide in all compartments other than the
TABLE 3
Model-Predicted Perchlorate Dose to the Pup from Maternal
Drinking Water Exposure on PND 10
Maternal dose
(mg/kg-day)
Pup dose
(mg/kg-day)
Relative pup dose
(% maternal dose)
0.01
0.1
1.0
10.0
0.07
0.66
2.82
9.08
49.9
45.8
19.0
6.3
thyroid and plasma. Simulations were performed against total
radioiodide concentrations in extrathyroidal tissues and against
inorganic and incorporated iodide in thyroid and serum. Despite this simplification, the model is able to describe radiodide
data in maternal and neonatal tissues from PND 5 through 18
over doses spanning more than four orders of magnitude, as
well as distribution data from dietary iodine intake. Thus, the
model description of extrathyroidal tissue iodide uptake based
on the transfer of inorganic iodide via NIS predicts the data
reasonably well without the added uncertainty or complexity of
significant contribution from the uptake of incorporated radioiodine by extrathyroidal tissues.
Although preliminary extrapolation of the acute iodide kinetic model to long-term exposure scenarios compares favorably with the data, this model does not yet address the feedback
mechanisms involved in maintaining normal iodine homeostasis. However, the model predicted interaction between dietary
and administered radioiodide does indicate that the small variations in laboratory rat chow expected between studies should
not affect model predictions of radioiodide distribution or
perchlorate-induced inhibition of thyroid radioiodide uptake.
At the dietary intake required to affect competition for NIS,
serum levels would be high enough (⬎250 ␮g/l) to trigger a
response from the thyroid known as the Wolff-Chaikoff effect,
wherein the thyroid appears to expel inorganic iodide from the
cells (Wolff and Chaikoff, 1948). In order to address cases of
dietary iodine excess or deficiency, future elaborations of the
model would have to include a more detailed description of
hormone distribution, homeostasis, and regulation. However,
the present model should be useful for predicting tissue dosimetry and inhibition of thyroid iodide uptake in the rat and
for extrapolation to the average human with a normal iodide
diet.
The PBPK model described here also successfully repro-
PBPK ClO 4 ⫺ MODEL FOR RAT LACTATION
TABLE 4
Model Predicted Internal Dosimetrics: Serum ClO 4 ⴚ AUC
(mg/l) in Male, Pregnant, Fetal, Lactating, and Neonatal Rat from
Drinking Water Perchlorate Exposure
GD 20
PND 10
ClO 4 ⫺ dose
(mg/kg-day) Male rat Pregnant rat Fetal rat Lactating rat Neonate rat
0.01
0.1
1.0
10.0
0.05
0.16
0.60
1.52
0.05
0.17
0.61
1.56
0.02
0.10
0.32
0.62
0.06
0.22
0.65
4.63
0.03
0.14
0.54
1.72
duces measured perchlorate and radioiodide distribution kinetics in the lactating rat and neonate. The model simulates ClO 4 ⫺
distribution and transfer via breast milk with reasonable accuracy in drinking water exposures ranging over three orders of
magnitude (0.01–10.0 mg/kg-day) and at two time points in
lactation, PND 5 and 10. In the absence of acute perchlorate
kinetic data in rat lactation, we rely on the consistency of this
model structure and its parameters with those of the male rat
(Merrill et al., 2003), which successfully describes such data.
Having accounted for differences in physiology due to lactation, most of the remaining chemical-specific parameters remain essentially unchanged from those of the adult male rat.
Therefore, we can assume that, like the male rat model, the
acute perchlorate kinetics can be adequately described with
model structure based on iodide kinetics. This is further supported by the ability of the model to predict acute iodide
inhibition kinetics, as inhibition of thyroid uptake is dependent
on free serum perchlorate levels. Additionally, in terms of
exposure route, drinking water dosing is actually more relevant
to the risk assessment. Thus, the model is able to describe
distribution to the target tissues and in the serum resulting from
exposure via the route that is most applicable to that of humans. The accuracy of the model ClO 4 ⫺ description allows us
to answer two vital questions in determining risk across life
stages: (1) the dose to the neonate and (2) the relative sensitivity, with respect to tissue dose and thyroid iodide inhibition,
compared to the nonpregnant and pregnant adult, as well as to
the fetus (Tables 3 through 5).
Experiments in our laboratory have confirmed that perchlorate was indeed transferred to the pup through suckling by the
detection of ClO 4 ⫺ in milk, as well as in the neonate serum, GI
contents, and skin (Fig. 2). However, the small number of data
points and the difficulty in determining ingestion of milk, loss
through urinary clearance, and other competing processes
made the determination of neonatal dose quite difficult by
classical methods. Because the model accounts for physiological and kinetic differences, it is able to provide a reasonable
estimate of a previously uncharacterized measure of risk,
ClO 4 ⫺ dose to the neonate (Table 3). In fact, the model predicts
that the pup receives a sevenfold greater perchlorate dose than
the dam on PND 10 when adjusted for body weight at the
431
lowest experimental dose (0.01 mg ClO 4 ⫺/kg-day). This difference between the maternal and neonatal dose disappears,
however, at higher doses (10 mg ClO 4 ⫺/kg-day), where toxicity would be expected.
Additional calculations were performed with the model to
determine the AUC for perchlorate in serum across doses and
life stages. Serum, rather than thyroid, perchlorate concentration was designated as a dose metric for life-stage and species
comparison. Perchlorate’s action on the thyroid is the inhibition of iodide uptake, leading to diminished intrathyroidal I –
levels and potentially decreased hormone production. Since
thyroid iodide uptake inhibition is dependent on serum ClO 4 ⫺
levels, this variable was determined to be a more appropriate
dose metric by which to judge relative sensitivity to later
effects. By comparing these measures of average serum concentrations across life stages, valuable insight can be gained
regarding relative sensitivity to perchlorate exposure. Thus it is
evident that, despite the increased dose to the neonate (0.07 vs.
0.01 mg/kg-day in the adult), the PND 10 pup serum average
ClO 4 ⫺ concentrations are consistently lower than those of the
adult. In fact, a comparison across life stages reveals that the
serum ClO 4 ⫺ concentrations of the lactating dam were slightly
higher than the male, pregnant, fetal, or neonatal rat, suggesting that lactation may be the time period with the greatest
internal perchlorate exposure. This increased serum concentration of ClO 4 ⫺ in the lactating rat, suggested by both model
simulations and measured data, is somewhat surprising, considering the additional clearance route provided through the
milk, and is likely due to increased serum binding (Iino and
Greer, 1961).
In developing the perchlorate thyroid model, some assumptions were made concerning the mode of action, as well as in
the designation of values for some of the parameters. The
model structure is highly dependent on the chosen definition of
the mode of action, which in the case of perchlorate involves
the competitive binding of the perchlorate ion to NIS, resulting
in diminished I – thyroidal uptake and the active concentration
of ClO 4 ⫺ in the thyroid cells. Although it has been suggested
that ClO 4 ⫺ may not be transferred into the thyrocytes based on
electrogenicity studies in oocytes (Soldin, 2002), the larger
body of evidence suggests otherwise. Specifically, published
TABLE 5
Model Predicted Internal Dosimetrics: %Inhibition of Thyroid
Iodide Uptake in Male, Pregnant, Fetal, Lactating, and Neonatal
Rat from Acute Perchlorate Exposure
ClO 4 ⫺ dose
(mg/kg/day) Male rat Pregnant rat Fetal rat Lactating rat Neonate rat
0.01
0.1
1.0
10.0
1.7
17.9
76.0
90.6
2.5
25.4
87.1
93.4
4.1
36.0
88.8
95.7
0.3
3.4
49.0
92.5
0.4
4.4
53.8
94.9
432
CLEWELL ET AL.
studies with both radiolobeled and cold perchlorate consistently report thyroid: serum ratios that are greater than 1 and as
much as 30 (Chow and Woodbury, 1970; Clewell et al., 2002b,
2003; Yu et al., 2002). Furthermore, ClO 4 ⫺ has been shown in
studies in our laboratory to be concentrated in all of the
measured extra-thyroidal tissues known to contain NIS, including the GI contents, skin, and milk (see Fig. 2 and Clewell et
al., 2002b; Yu et al., 2002). A more detailed justification for
the use of competitive inhibition is available elsewhere
(Clewell and Gearhart, 2002b).
Thus, this model structure is based upon competitive inhibition of iodide at the symporter. However, despite the obvious
influence this interpretation has on predicted internal thyroid
ClO 4 ⫺ levels, it actually has very little influence on the either
thyroid iodide inhibition or serum ClO 4 ⫺ levels. Since the
relative thyroid volume is very small, the total amount of
chemical is quite low in spite of the high concentrations.
Therefore, large changes in predicted thyroid concentrations do
not significantly affect blood levels. Additionally, the ability of
ClO 4 ⫺ to inhibit iodide uptake is based on the relative affinities
and the amount of free ClO 4 ⫺ in the blood, rather than the
amount of perchlorate in the thyroid itself. Thus, the active
uptake of perchlorate into the thyroid cells, though included for
pharmacokinetic accuracy, does not affect the usefulness of the
model for comparing life-stage and species differences in the
precursors to hormone disruption.
Linking the perchlorate and iodide models via competitive
inhibition at the symporter also enables the model to predict
ClO 4 ⫺–induced inhibition of iodide uptake in the maternal and
neonatal tissues after acute ClO 4 ⫺ exposure in the lactating rat.
Because ClO 4 ⫺ has a greater affinity for NIS than I –, it effectively inhibits uptake not only into the thyroid, but also into the
milk, stomach, and skin. The model accurately predicts data on
this inhibition of iodide uptake in the maternal thyroid mammary gland and milk from our studies and those of Potter et al.
(1959). Although data are not available directly in the neonate,
confidence in the model predictions is increased by the ability
of the maternal model, as well as the previously described
sister models in the male, pregnant, and fetal rat (Clewell et al.,
2003; Merrill et al., 2003), to describe this inhibition using the
same mechanistic construct and validated chemical-specific
parameters. Thus, the model provides a means for estimating
neonatal inhibition of thyroid iodide in the absence of such
data.
The ability of ClO 4 ⫺ to reduce iodide levels in the milk, as
well as uptake in thyroid, presents a potentially increased
health risk to the neonate. In order to quantitatively determine
the effect of maternal ClO 4 ⫺ exposure on the transfer of iodide
in breast milk and subsequent neonatal thyroid levels, the
model predicted percent inhibition in maternal and neonatal
thyroids were compared to those generated for the male, pregnant, and fetal rat with the models of Merrill et al. (2003) and
Clewell et al. (2003). In spite of the multiple inhibition sites
(mammary gland, milk, and thyroid), inhibition in the neonatal
thyroid was similar to that of the dam. This may be due to the
fact that neonatal serum perchlorate levels are less than those
of the dam. From the model estimates given in Table 5, the
neonate shows less perchlorate-induced inhibition of thyroid
iodide uptake compared to the other life stages in the rat.
Model estimates suggest that the fetal rat thyroid is most
vulnerable to inhibition, with a tenfold greater inhibition than
the neonate at the lowest measured dose (0.01 mg/kg ClO 4 ⫺).
Thus, it is possible to utilize these pharmacokinetic models
to develop reasonable estimates of internal dose metrics based
on quantitative biological concepts and a variety of data collected in different conditions, species, and life stages. The
chosen dose metrics are measures of internal dose, and should
be better indicators of relative risk than external dose (i.e.,
perchlorate intake). However, these internal dose metrics are
merely measures of the precursor kinetics and do not give a
complete picture of perchlorate’s affect on hormone homeostasis. Indeed, determining which life stage is at greatest risk
actually depends on the chosen precursor dose metric. Of those
presented in this article, utilizing serum ClO 4 ⫺ levels indicates
that the lactating dam is at highest risk, while thyroid iodide
inhibition suggests the fetus is the most sensitive life stage.
In reality, many factors must be taken into consideration
when assessing the risk associated with perchlorate exposure.
For example, although the predicted thyroid inhibitions across
life stages indicate that the fetal thyroid is most vulnerable,
overall risk to the fetus may actually be less than that of the
neonate. This is due to the fact that inhibition of thyroid iodide
uptake is only a precursor to hormone disruption. In gestation,
maternal thyroid hormones are available to the fetus, as opposed to lactation, where the neonate is responsible for its
hormone synthesis. Therefore, the maternal hormones may
compensate for the increased inhibition seen in the fetal thyroid
resulting in less chance of adverse developmental effects. In
fact, in the developmental studies of York et al. (1999, 2001),
the pregnant dam showed the greatest change in serum TSH
and T 4 levels. Thus, it is possible that the additional pharmacodynamic interactions (hormone synthesis, metabolism, etc.)
could result in a relative risk profile not at all suggested by the
preliminary measurements of tissue dose or pharmacokinetic
perturbations. For this reason, further elaboration of these
models to include hormone homeostasis and the pharamocodynamic interactions is critical to improve the risk assessment
for perchlorate.
This model allows the integration of a wide variety of
physiological, biochemical, and dosimetry information, to produce parameter estimates consistent with measured perchlorate
and iodide kinetic data during important periods of development. In order to further assess model performance, other
analytical tools can be applied to the model, including statistical evaluation of the goodness of model fit to present data
sets, more comprehensive sensitivity analyses for multiple
dosimetrics and assessment of the effects of parameter variability on dose measures. Sensitivity analysis (Fig. 11) pro-
PBPK ClO 4 ⫺ MODEL FOR RAT LACTATION
vides insight into the relative importance of model parameters
with respect to specific measures of dose. The variability
analysis, performed with known distributions for model parameters, allows the prediction of likely ranges of the dosimetrics
within a human population. For the application of risk assessment, incorporation of a more comprehensive evaluation of
variability of the more sensitive model parameters will be more
important than a formal estimation with the present data sets.
An informative use of this PBPK model is in the correlation
of predicted internal dosimetrics to periods in gestation where
perchlorate exposure and/or iodide deficiency has been associated with developmental effects. The model can be used to
predict tissue dosimetry in effects studies and to pinpoint
specific times in development fetal/neonatal iodide uptake is
most critical.
Further elaboration of these models to extrapolate dosimetry
to humans has been explored elsewhere (Clewell et al., 2001;
Clewell and Gearhart, 2002a). Together with the models of
Merrill et al. (2001, 2003) and Clewell et al. (2003), this model
can be used to approximate species and life stage kinetic
differences at specific doses. Furthermore, since these PBPK
models to relate complex pharmacokinetic variables back to
the basic physiological and biochemical parameters that are
often measurable, we can use the comparative information
provided by the PBPK models about the chemical kinetics to
develop quantitative estimates of species and life stage differences. Thus, it is possible to extrapolate these models to the
population of interest (human gestation and lactation), in order
to run simulations for sensitive human populations at a variety
of exposure scenarios to estimate internal dose (Clewell et al.,
2001).
APPENDIX
The following equations represent the distribution of iodide
within the thyroid, in the absence of competitive inhibition
(Equations 1– 6). Perchlorate uptake into the thyroid is described similarly, but without the organification (ClProd i) and
hormone secretion (ClSecr i) terms.
RATS i ⫽ QT ⴱ 共CA i ⫺ CTS i 兲
⫹ PATF i ⴱ
冉
RATF i ⫽ RupTF i ⫹ PATF i ⴱ
⫹ PATL i ⴱ
冉
冊
CTF i
⫺ CTS i ⫺ RupTF i
PTF i
冉
冊
CTS i ⫺
冊
CTF i
⫺ RupTL i
PTF i
CTL i
⫺ CTF i ⫺ 共ClProd i ⴱ CTF i 兲
PTL i
RATL i ⫽ RupTL i ⫹ PATL i ⴱ
冉
(1)
CTF i ⫺
CTL i
PTL i
冊
(2)
(3)
433
RupTF i ⫽
VmaxTF i ⴱ CTS i
KmT i ⫹ CTS i
(4)
RupTL i ⫽
VmaxTL i ⴱ CTF i
KmTL i ⫹ CTF i
(5)
RAbnd i ⫽ 共ClProd i ⫻ CTF i 兲 ⫺ 共ClSecr i ⫻ CTbnd i 兲
(6)
RATS i, RATF i, RATL i, and RABnd i are the rates of change in
the amount of inorganic iodide in the thyroid stroma, follicle,
colloid (lumen) and the rate of change in the amount of organic
or incorporated iodine in the total thyroid, respectively. PATF i,
PATL i, and PTF i, PTL i are the PAs and effective partition
coefficients for the stroma:follicle and follicle:colloid membranes, respectively. RupTF i and RupTF i are the active uptake
rates of iodide into the follicle and colloid. VmaxTF i, VmaxTL i
and KmTF i, KmTL i are the maximum velocities and affinity
constants for transport of iodide into the follicle and colloid.
QT represents fractional blood flow to the thyroid capillary
bed. CA i, CTS i, CTF i, CTL i, and CTbnd i are the iodide concentrations in arterial plasma, thyroid stroma, follicle, colloid,
and the incorporated (organified) iodine compartment, respectively.
The inhibited thyroid is described in the same manner as
shown above, except that the M-M terms for active uptake are
modified to account for competitive inhibition. The following
equation gives an example of the description of competitive
inhibition of iodide uptake by perchlorate. As before, RupTF i
represents the rate of active iodide uptake into the thyroid
follicle. This rate is modified by the affinity of transport mechanism in the follicle for ClO 4⫺ (KmTF p) and the concentration
of ClO 4 ⫺ in the stroma (CTS p). Inhibition of iodide uptake in
other tissues with NIS is described in the same manner as the
thyroid follicle inhibition.
RupTF i ⫽
VmaxTF i ⴱ CTS i
CTS p
KmTF i ⴱ 1 ⫹
⫹ CTS i
KmTF p
冉
冊
(7)
The model description of uptake iodide uptake in the milk
with competitive inhibition at both transporters is shown in
Equations 8 through 12. Equations for perchlorate would be
similar, but without the terms for competitive uptake. RAMB i,
RAM i, and RAMk i are the rate of change in the amount of
iodide in the mammary gland capillary blood, the mammary
gland tissue, and the milk, respectively. RupM i and RupMk i
represent the rate of active uptake of iodide into the mammary
gland and the milk. VmaxM i, VmaxMk i and KmM i, KmMk i are
the maximum velocities and affinity constants for the active
transport of iodide into the mammary gland and milk. QM
represents fractional blood flow to the mammary gland capillary bed. PAM i, PAMk i, PM i, and PMk i are the permeability
area cross products and partition coefficients used to describe
434
CLEWELL ET AL.
the passive diffusion of iodide between the capillary blood and
mammary gland, and the mammary gland and milk, respectively. CA i, CMB i, CM i, and CMk i are the iodide concentrations in arterial plasma, mammary capillary blood, mammary
gland and milk. Ktrans represents the rate of milk production,
which is assumed to be equal to the suckling rate.
RAMB i ⫽ QM ⫻ 共CA i ⫺ CVMB i 兲 ⫹ PAM i
⫻
冉
冉
冊
CM i
⫺ CVMB i ⫺ RupM i
PM i
RAM i ⫽ PAM i ⫻ CVMB i ⫺
CM i
PM i
冊
⫹ RupM i ⫺ RupMk i ⫹ PAMk i ⫻
冉
冉
RAMk i ⫽ RupMk i ⫹ PAMk i ⫻ CM i ⫺
CMk i
⫺ CM i
PMk i
CMk i
PMk i
冊
冊
⫺ 共Ktrans ⫻ CMk i 兲
RupM i ⫽
RupMk i ⫽
VmaxM i ⴱ CMB i
CMB p
KmM i ⴱ 1 ⫹
⫹ CMB i
KmM p
冉
冊
VmaxMk i ⴱ CM i
CM p
KmMk i ⴱ 1 ⫹
⫹ CM i
KmMk p
冉
冊
(8)
RupGJi ⫽
(11)
(12)
The model description for active uptake of iodide into the GI
contents with competitive inhibition by ClO 4 ⫺ is given in
Equations 13 through 16. The skin compartment is modeled in
the same manner. Equations for perchlorate would be similar to
those of iodide without the terms for competitive inhibition.
Here RAGB i, RAG i, and RAGJ i represent the rates of change in
the GI capillary blood, GI tract and GI contents, respectively.
QG is the regional blood flow to the GI, RMR is the rate of oral
dosing, and CGB i, CG i, and CGJ i are the total iodide concentration in the GI blood, tract and contents. Finally, partitioning
of iodide between the GI blood and tract and the GI tract and
contents is described using the partition coefficients (PG i and
PGJ i) and permeability area cross products (PAG i and PAGJ i).
(16)
Model equations for compartments without active uptake
(shown for the liver, Equation 17) were modeled in the as
flow-limited, using only partitioning and blood flow to control
tissue iodide and perchlorate concentrations. In the following
equations, RAL i is the rate of change in the amount of total
iodide in the liver, QL is the fractional blood flow to the liver,
CL i is the concentration of iodide in the liver, and PL i is the
blood:liver partition coefficient. The kidney and fat are modeled similarly.
RAL i ⫽ QL ⫻ 共CA i ⫺ CL i /PL i 兲
(9)
(10)
VmaxGJ i ⫻ CG i
KmG i ⫻ 共1 ⫹ CG p /KmG p 兲 ⫹ CG i
(17)
Model equations describing iodine in the arterial blood are
given below (Equations 18 –19). Where RaBnd i and RaIncorp i
are the rates of change in amount of iodide bound to plasma
proteins and hormone incorporated iodine, respectively.
VmaxB i and Km i are the Michaelis-Menten terms for saturable
binding of inorganic iodide to plasma proteins. Km p is the
affinity constant for the binding of ClO 4 ⫺ to plasma proteins,
which is used to adjust the affinity of iodide in order to
mathematically describe the competitive inhibition of the anions for binding sites. Clunb i, Clsecr i and Cldeiod i are the first
order rate constants for the dissociation of I – from plasma
proteins, the secretion of thyroid hormones (hormone incorporated iodine) form the thyroid and the whole-body deiodination
of thyroid hormones, respectively. CA i and CA p are the concentrations of free inorganic iodide and free ClO 4 ⫺ in the
plasma. The binding of perchlorate to plasma proteins would
be described in the same manner as iodide (Equation 18).
Rabnd i ⫽
共VmaxB i ⫻ CA i 兲
共KmB i ⫻ 共1 ⫹ 共CA p /KmB p 兲兲 ⫹ CA i 兲
⫺ 共Clunb i ⫻ CAbnd i 兲
(18)
RaIncorp i ⫽ 共ClSecr ⫻ CTbnd i 兲
⫺ 共ClDeiod ⫻ CAIncorp i 兲
(19)
ACKNOWLEDGMENTS
RAGB i ⫽ QG ⫻ 共CA i ⫺ CVGB i 兲
⫹ PAG i ⫻ 共CG i /PG i ⫺ CVGB i 兲
(13)
RAG i ⫽ PAG i ⫻ 共CVGB i ⫺ CG i /PG i 兲
⫹ PAGJ i ⫻ 共CGJ i /PGJ i ⫺ CG i 兲 ⫺ RupGJ i
(14)
RAGJ i ⫽ RupGJ i ⫹ PAGJ i ⫻ 共CG i ⫺ CGJ i /PGJ i 兲
⫹ RMR i
(15)
The authors would like to thank Tammie Covington, Harvey Clewell, Dr.
Melvin Andersen, and Dr. Peter Robinson for their modeling advice; Latha
Narayanan and Gerry Buttler for sample analyses; Charles Goodyear for
performing statistical analyses of the data; and Dick Godfrey, Peggy Parish,
Susan Young, TSgt Todd Ligman, MSgt Jim McCafferty, Tim Bausman, SSgt
Paula Todd, and MSgt Rick Black for technical support. The authors would
like to acknowledge Annie Jarabek, LtCol Dan Rogers, Dr. David Mattie, Dr.
Richard Stotts, and the U.S. Air Force for their support of this project and the
U.S. Navy for financial support.
PBPK ClO 4 ⫺ MODEL FOR RAT LACTATION
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