The effect of ethanol on the transport of amino acids across the human placenta was studied in the dual perfusion apparatus using a non-metabolizable α-amino isobutyric acid (AIB). Results were obtained for thirty intact whole human placentas in the absence (control group) and presence (ethanol group) of ethanol (500 - 1000 mg/dL). Experimental determinations of AIB transport at AIB concentrations of 5 - 100 mg/l, measured radioactively using (1 −14 C-) AIB, were compared with a dual-active transport model. The diffusion coefficients of AIB were found to be (3.7 × 10 −9 cm 2/s) in the absence of ethanol and (2.3 × 10 −9 cm 2/s) in the presence of ethanol with no statistical difference ( P = 0.25). The ratio of the fetal to maternal perfusate concentrations in the absence of ethanol (1.44) was statistically significant ( P = 0.016) from the ratio in the presence of ethanol (1.20), which may indicate that active transport in the human placenta is inhibited by the presence of ethanol. The placental uptake from the maternal circulation was 2.6 (control) and 2.5 (ethanol) times greater than the uptake from the total circulation. The relative contribution of the diffusive transport to the net placental uptake of AIB from both the maternal and fetal circulations was less than that of active transport regardless of the presence of ethanol: control (38%) and ethanol (35%). It appears that the placental tissue plays the role of a mediator to maintain a fetal concentration higher than the maternal one by either enhancing the transfer from the maternal to the placental tissue or impairing the transfer in the opposite direction.
The placenta is the site of absorption and transfer of nutrients for fetal growth and development. In addition, it metabolizes nutrients for its own use [
Although qualitative and quantitative differences probably exist between placentas at different stages of pregnancy, the term placenta (which is one of the rare human organs readily available for the in vitro study) can serve as a valid tool for the study of nutrient transport [
In this study, experimental results from the perfusion of the whole human placenta at term were presented with the purpose of understanding the transplacental transport of amino acids in the absence or presence of ethanol, using a non metabolizable amino acid analog ( -amino isobutyric acids: AIB). A one-dimensional mathematical model with three compartments was also constructed to characterize the amino acid transport mechanism in the human placenta.
The inaccessibility of the human placenta in pregnancy effectively excludes any direct examination of its transfer function, and although animal models have contributed greatly to a general understanding of placental function there are major interspecies differences, and similarity of behavior with humans can never be assumed. The obvious alternative is to exploit the placenta when it becomes available after delivery, but that portion presents great technical difficulties [
Placental nutrient transport plays a vital role in the development of the embryo and fetus. In humans, the placenta and fetal circulation form during the early weeks of embryonic life. The placenta then continues to develop, growing in size, changing morphologically, and altering transport activities until at term it weighs about one seventh that of the fetus. Although substances can move between maternal and fetal circulations via the amnion or the yolk sac, near term the chorionic membranes probably account for the majority of total nutrient transport.
Isolated chorionic villi | [ 13 ] |
---|---|
Tissue slice | [ 3 ] |
Membrane vesicle | [ 14 ] |
Homogenates | [ 15 ] |
Perfusion | [ 16 , 17 ] |
Simple diffusion | Oxygen, carbon dioxide, fatty acids, steroids, nucleosides, electrolytes, fat soluble vitamin |
---|---|
Facilitated diffusion | Sugars, glucose |
Active transport | Amino acids, some cations, water soluble vitamin |
Solvent drag | Electrolytes |
Pinocytosis | Proteins |
and the mechanisms believed to be responsible for their transport [18 , 19]. Extensive reviews about the transport of amino acids were reported by Yudilevich and Sweiry (1985).
There are two mechanisms for the movement of amino acids across the placenta: active transport and passive diffusion [
Neutral amino acids can be concentrated in both the trophoblast and fetal blood. This concentration is stereo specific and energy dependent. The neutral amino acid, -amino isobutyric acid (AIB), has been a useful marker for the characterization of these amino acid transport processes in the placenta because it is not metabolized. Because of this fact, AIB has been frequently used as an analog for naturally occurring amino acids [3 , 26 , 27]. AIB is known to be non-metabolizable, energy dependent, saturable, and transported in the same glutamine [
The asterisk (*) indicates the radioactive form of AIB, which is then called α-amino (1-C14) isobutyric acid.
Directionality of AIB transport from maternal to fetal circulations was demonstrated in the dually-perfused human placental lobule [20 , 28]. After 4 hours of perfusion, placental AIB concentration measured at the end of perfusion was 2.3 - 2.8 fold greater than that in maternal or fetal plasma, while the ratio of fetal to maternal plasma was 1.21 [
In 1973, Smith et al. reported the first Michaelis-Menten kinetic analysis in human placental villous fragments. A two component uptake pattern was observed over the concentration range 0.1 - 5 mM with a saturable part and a nonsaturable linear component. Incubation of the tissues in amino acid free medium 3 hours prior to kinetic measurements halved the and trebled V max . Miller and Berndt (1974) showed in human placental slices that AIB concentration was saturable over a narrower concentration range of 0.1 - 0.8 mM, when the ouabain-insensitive component was subtracted from the total uptake. Rapid (2 min) AIB uptake in human microvillous membrane vesicles, again with a two component flux pattern, gave comparable kinetic parameters [
The main intoxicant in alcoholic beverages is ethyl alcohol or ethanol.
Ethanol reaches the blood quickly and is distributed almost uniformly throughout the body [
The use of ethanol to prevent premature labor served to initiate research on the acute effect of ethanol on the fetus. The maternal and fetal perfusate ethanol concentration time curves were virtually superimposible during the perfusion, and also the placental tissue ethanol concentration measured at the end of perfusion was close to the perfusate concentration [
Biomedical engineering illustrates the application of engineering in the service of medicine and biology [
In process response analysis, the process and the input are defined and the desired information is the response of the process to the input. Process control problems are examples of this type of operation. Process synthesis problems generally relate to process design, where the process input and output are known and the objective is to find the best route for achieving the desired output. The third type of operation can be termed process input analysis. In this case, the process and the response are known and the process input is desired.
The most common case, especially in biomedical engineering, is the second type. One type of mathematical model used to simulate unknown processes has been the so called “compartment” type. The most common way of applying these models is to try to find the parameters of a sufficient number of compartments in order to fit the experimental data. If the intercompartment transfer is assumed to take place following a linear law, which could be mass flow or diffusion, the balances have the form:
d C i / d t = ∑ j = 0 ∞ K i j × C i j ( i = 1 , ⋯ , n ) (1)
For constant K i j , the solution of Equation (1) is known to be a series of exponentials:
C i = ∑ j = 0 ∞ A i j × exp ( B j t ) . (2)
In 1966, Bischoff and Brown studied drug distribution through the circulatory system in mammals. They assumed the tissue was composed of three main types of local regions: capillaries, interstitial fluid, and cells. These were treated as individual compartments and their assembly was used to simulate a larger region. In 1973, Hill and Young studied carbon dioxide transfer in the human placenta using a 4-compartment model for placental vessels: maternal erythrocytes, maternal plasma, fetal plasma, and fetal erythrocytes. In 1974, Reneau et al. developed a lumped parameter model by dividing each fetal organ into two compartments, one for the capillary bed and one for tissue. The placenta was divided into one compartment for the fetal side and another for the maternal side. Volume lumps were placed along the major veins and arteries to account for blood volume and to obtain time delays. Equations were derived using a stirred tank analysis and were solved by means of a digital simulation language CSMP (Continuous System Modeling Program).
In 1974, Hlavinka developed a multi-compartmental patient artificial kidney model to characterize inner body transport during hemodialysis. The blood concentrations of Dextran and Vitamin B-12 were used to determine model parameters, which were searched for by a fourth order Runge-Kutta integration routine until the model best fitted the data. The transcapillary mass transfer coefficients for Dextran and Vitamin B-12 were 502 and 470 ml/min, respectively. Similar approaches were attempted by Popovich et al. (1975). All the compartmental models should be based on physiologically meaningful quantities such as volume, flow rates, system parameters, and not derived by a curve fitting to an arbitrary set of functions. None of the above compartmental approaches were considered “active transport”.
Whole placentas with undamaged maternal surfaces and fetal circulations were obtained from the Crouse-lrving Memorial Hospital, which has over 3500 deliveries per year. These normal term placentas from either Caesarian or spontaneous labor delivery were perfused with Krebs-Ringer Bicarbonate (KRB) solution within fifteen minutes after delivery. The umbilical cord was diagonally cut 3 - 4 cm up from the chorionic plate to eliminate the effect of umbilical vessel plasms on fetal flow and to reveal the individual vein and arteries for easy cannulation. Silicone rubber cannulae (8 fr. for arteries and 12 fr. for vein) were inserted up to the anastomosis of the umbilical arteries and tied in place with a cotton string. If the amount of fetal volume loss from the fetal circulation toward the maternal circulation was less than 5 ml/min out of 30 ml/min, it was assumed that the placenta was being adequately perfused. The perfusion apparatus [
AIB was added in the nonradioactive form (Sigma Chemical, St. Louis, MO) and as a radioisotope (Amersham, Arlington Heights, IL). (C14-) AIB (57 mCi/mmol) were used with dilution (1 - 5 μCi). The concentrations of perfusate AIB was sequentially changed every one to two hours during experiments of up to 5 hours long. The variables measured during the course of the run were the concentrations of ethanol (~1000 mg/dL) and AIB (5 - 200 mg/l). Tissue concentrations of AIB and ethanol were determined from three tissue samples taken at the end of each run.
In one set of experiments AIB was added to either the maternal or the fetal circulations (single addition technique). In another set of experiments AIB was added simultaneously to both circulations to speed up the formation of the fetal maternal gradient (dual addition technique). The results from the dual addition technique were used to determine not only the net kinetic parameters but also the individual kinetic parameters of Km and Vmax for the uptake from each circulation with and without ethanol. In this way the study could characterize the asymmetry of the transplacental AIB transport mechanism in the absence and presence of ethanol.
1 ml perfusate samples mixed with 1 ml 5% trichloroacetic acid (TCA) was centrifuged at 300 rpm for 10 minutes, and 1 ml of each supernatant was placed in a 5 ml plastic vial (Sarstedt, West Germany) with a 4 ml liquid scintillation cocktail (Ready-Solv CP, Bechman). The selection of 5% TCA was based upon the study of Bentler [
Steady state measurements have the advantage of simplicity and straight forward interpretation if it is known beforehand that the transport of a substance is flow limited or the flow pattern corresponds to one of the cases considered. Whole placental perfusion steady state measurements require very large volumes of perfusate particularly for the maternal side since the perfusion times are several hours long. The way to overcome this difficulty and the unsteady state model for the transport of diffusion limited substances such as AIB is shown below. In the unsteady state models, the quantity of substances present in the placental tissue can change with time and this change is taken into account by considering a placental tissue as a separate compartment.
The unsteady state transport models are based upon interpreting the perfusion system and the placenta. The placenta itself is thought of as a series of identical villous capillaries, all of which are perfused in parallel at identical flow rates. The fetal flow rate to these capillaries is less, however, than the fetal flow rate from the fetal reservoir since anatomical evidence and clearance measurements of others [45 , 46] indicate that a fraction of the fetal flow to the umbilical arteries is shunted directly back to the umbilical vein without ever passing through the villous capillary bed.
The maternal perfusate flows over these capillaries. In these experiments, because the maternal perfusate flow rate is much higher than the fetal perfusate flow rate (600 ml/min vs. 30 ml/min), the concentration change of the maternal perfusate in a single pass is much smaller than the fetal change. Consequently, the maternal concentration in the placenta is nearly constant at any time and the flow direction of the maternal perfusate relative to the fetal perfusate is unimportant. Convective transport of the fetal perfusate through channels in the placenta to the maternal perfusate is assumed to account for the transfer of fluid from the fetal to the maternal circulations during perfusion. The several types of placental tissue (syncytiotrophoblast, connective tissues, capillary endothelium) are lumped together into a single composite placenta tissue of volume V p with uniform concentration C p . This approximation introduces little error for the transfer of flow limited substances since these substances rapidly equilibrate to essentially the same concentration in the maternal perfusate, placental tissue, and fetal perfusate. Because the flow rate of the maternal perfusate is so much higher than the flow rate of the fetal perfusate, the equilibrium concentration becomes essentially equal to the maternal concentration.
For substances whose transport is given by diffusion or other more complicated processes, the lumping approximation is not reasonable. Amino acids such as AIB are actively transported into the trophoblast cell layer and perhaps the capillary endothelium. Exchange across the cell walls also occurs by diffusion. The major resistance to transport across these two placental layers is expected to be in the cell walls, which are lipid in nature, rather than in the cytoplasm of the cells. Thus, three distinct concentrations may be present in the placental tissue; one for the syncytiotrophoblast, one for the connective tissue, and one for the capillary endothelium. Depending on the resistance of the various cell membranes, these concentrations could be nearly the same or distinctly different. Thus, theoretically an arrangement could be made for a more complicated model taking the several tissue layers in account. On the other hand, only one tissue concentration can be measured experimentally i.e., a concentration representing the composite concentration of the tissue. Thus in the interests of simplicity, only one tissue layer was considered here for AIB transport.
The transport of AIB in the placenta is complex consisting both of an active transport mechanism and a diffusive process. An estimate of whether the fetal flow rate has any significant effect on the rate of transport can be obtained by comparing the time for AIB transport processes into the tissue, T s , with the residence time of the fetal perfusate in the capillary bed, T r . The effective time for transport into the tissue can be determined (Bassingwaighte and Winkler, 1982) by using an estimate of its effective diffusion coefficient as;
T s = 4 L 2 / D . (3)
where L and D are the effective thickness of diffusion barrier and the effective diffusion coefficient, respectively. For a transport barrier thickness of approximately 13 μ accounting for 10 μ of villous membrane thickness [
T r = V c Q c = 40 15 = 2.7 minutes . (4)
Consequently, the changes in the fetal perfusate concentration during a single pass is not expected to be large compared to the fetal reservoir concentration and the fetal fluid in the villous capillary will be approximately equal to the concentration in the fetal reservoir. Active transport of amino acids is assumed to take place from both the maternal and the fetal perfusates according to arate expression of the Michaelis-Menten type;
Y k = V ′ max k C k C k + K k (5)
where V ′ max k and K k are maximum uptake and Michaelis constant of the “k”th compartment. This is equivalent to an enzyme carrier process located in the cell membrane which has a saturable number of sites and whose transport rate from one side of the cell membrane to the other is constant. This type of term is consistent with the expressions used by other investigators for guinea-pig [21 , 22 , 27], rat [
V m d C m d t = k 1 ( C p − C m ) − Y m + L f C f . (6)
V f d C f d t = k 1 ( C p − C f ) − Y f + L f C f . (7)
V p d C p d t = − V m d C m d t − V f d C f d t . (8)
The integral part of the equation from t = 0 (the first sample time) to the “n”th samples was used to calculate the placental tissue concentration of AIB ( C p ) from the changes in the concentrations and volumes in the maternal and fetal circulations. For this calculation the sample taken from the maternal and fetal reservoirs and the leak ( L f ) of maternal perfusate from the system was taken into account. Note that no AIB is present in the placental tissue when the first samples from both reservoirs are taken, i.e., ( V p C p ) = 0 .
The result is;
V p ≡ ( V p × C p ) n = { ( V m × C m ) i − ( V m × C m ) n } + { ( V f × C f ) i − ( V f × C f ) n } = L f ∑ i = 1 n − 1 ( C f ) i − { ( V m + V f ) i − ( V m + V f ) n } ∑ i = 1 n − 1 ( C m ) i (9)
where “Vp” is the uptake of placental tissue. Similarly, the placental uptakes from each circulation are given by;
V m = { ( V m × C m ) i − ( V m × C m ) n } + S m ∑ i = 1 n − 1 ( C m ) i = L f ∑ i = 1 n − 1 ( C f ) i − { ( V m + V f ) i − ( V m + V f ) n } ∑ i = 1 n − 1 ( C m ) i (10)
V f = { ( V f × C f ) i − ( V f × C f ) n } − ( S f + L f ) ∑ i = 1 n − 1 ( C f ) i . (11)
Laga et al. (1973) found that the average wet weight of placenta was 571 gm, while the trimmed volume was 448 cm3, the latter being determined by displacement of water in a 2-liter graduated cylinder [
V p = P w × 448 571 = 0.785 P w
The uptake at any time is divided by V p to determine the placental concentration ( C p ).
Net uptake rates available from the dual addition technique provide the net kinetic parameters with or without ethanol. Individual uptakes from the dual addition technique, however, provide individual kinetic parameters of each circulation as well as% individual uptakes from both the maternal and fetal circulations. That is,
% MaternalUptake = % Uptakefromthematernalside = 100 × U m / U p (13)
In the previous section, it is shown that the placental concentration ( C p ) can be determined experimentally. Let us now formulate an expression for C p using the proposed dual active transport model to represent the placental system in terms of measurable quantities and parameters. The placental uptake of AIB is given by;
V p d C p d t = ( Y m + Y f ) − k 1 ( C p − C m ) − k 1 ( C p − C f ) ; C p ( 0 ) = C p o . (14)
where Y m and Y f are the constant rates of maternal and fetal active transports corresponding to the constant AIB levels in each circulation. k 1 is the permeability of amino acid in the placenta. The integration of equation gives the simplified form;
C P − C P 0 = ( α − C P 0 ) ( 1 − e − β t ) . (15)
where
α = ( Y m + Y f ) + k 1 ( C m + C f ) 2 k 1 . (16)
β = 2 k 1 V p . (17)
C P 0 is expected to be zero for AIB at the beginning of each run.
The placental uptake of AIB as a function of time (t) is then given by;
V p = V p ( α − C P 0 ) ( 1 − e − β t ) . (18)
α , C P values are polynomially regressed with respect to the reciprocal of time until the regression coefficient approaches 1. The intercept of the regressed equation, corresponding to t → ∞ , gives an approximate value of α . C P values are normalized by this approximate value of α and Equation (15) shows that a plot of ln ( 1 − C p α ) vs. time (t), will be a straight line whose slope is then approximately − β . These approximate values of α and β serve as initial guesses of α and β for the nonlinear regression of Equation (14). The nonlinear regression package used is GAUSHAUS, whose scheme is based on the combined methods of the least squares and the steepest descent. Parts of its algorithm are similar to those reported by Booth (1949). Thus, the permeability ( k 1 ) from β and the net active transport rate ( Y m + Y f ) from α are determined, respectively. Utilizing these specific parameters, the relative contributions for the Fickian diffusion ( U d ) and the active transport ( U a ) processes upon the net placental uptake ( U p ) of AIB can be determined at any time where;
U p = U a − U d . (19)
Since the net uptake also is the sum of the individual uptakes from the maternal ( U m ) and the fetal ( U f ) circulations, the relative contribution of each process upon each circulation is calculated as;
U p = U m + U f . (20)
where
U m = U a m − U d m . (21)
U f = U a f − U d f . (22)
Thus, the individual uptake from maternal (m) or fetal (f) circulations by the processes of diffusion (d) or active transport (a) can be compared with each other.
Equations (6) to (8) are solved directly by numerical integration and the values of parameters ( K m , K f , V ′ max m , V ′ max f ) are varied until the experimental concentrations agree as much as possible with the ones predicted by the integration. The Gear (1971) method which is available from the IMSL routine is used. Its algorithm finds the approximations to the solution of a system of first order ordinary differential equations of the form y ′ = f ( x , y ) with initial conditions. The basic methods used for the solution are of the implicit linear multistep type, which are well described elsewhere [49 , 50].
There are two Equations (6) and (7), with four unknown parameters of K m , V ′ max m , K f and V ′ max f assuming k 1 is known from the pseudo-steady model. The degrees of freedom thus are four. Fitting the experimental data to the equations requires a minimization of the deviations of the predicted values from the experimental data. In order to develop constraints from a simple stability analysis and to provide good initial guesses for the minimization, which involves the numerical integration, the Laplace transform technique is used as follows.
Equations (6) to (8) are solved simultaneously by Laplace transform after linearizing Y with a Taylor series expansion in which only the first two terms are kept,
Y k = V max k C k o C k o + K k + Y ′ k ( C k o ) ( C k o ) ( C k o − C k o ) + Y ″ k ( C k o ) ( C k − C k o ) 2 2 ! + ⋯ (23)
where C m o is the initial concentration of “k”th compartment.
Y ′ k ( C k o ) = V max k K k / ( C k o + K k ) 2 . (24)
Y ″ k ( C k o ) = − 2 V max k K k / ( C k o + K k ) 3 . (25)
Thus,
Y k = V max k C k o C k o + K k + V max k K k ( C k − C k o ) ( C k o + K k ) 2 × [ 1 − 2 ( C k − C k o C k o + K k ) + ⋯ ] . (26)
If ( C k − C k o ) ≪ ( C k o + K k ) , i.e. C k ≪ ( 2 C k o + K k ) , Equation (26) can be approximated by truncating the second and higher order terms. This inequality is well satisfied in the present experiment. Thus,
Y k = V max k C k o C k o + K k + V max k K k ( C k o + K k ) 2 ( C k − C k o ) . (27)
Equation (27) can be simplified as;
Y k = θ k C k + δ k . (28)
where
θ k = K k Y k o C k o ( C k o + K k ) . (29)
and
δ k = C k o Y k o C k o + K k = C k o 2 θ k K k . (30)
Equations of (29) and (30) indicate that K k and V max k can be calculated once θ k and δ k are determined.
Equation (28) is substituted into Equations (6) to (8), and the steady state values can be obtained by setting, d C k / d t = 0 . The result is given by;
δ m = k 1 ( C p s − C m s ) − θ m C m s + L f C f s . (31)
δ f = k 1 ( C p s − C f s ) − θ f C f s + L f C f s . (32)
For the unsteady state, Equation (28) is substituted into equations of (6) to (8) giving;
d Z m d t = k 1 V m ( Z p − Z m ) − θ m Z m − L f Z f V m . (33)
d Z f d t = k 1 V f ( Z p − Z f ) − θ f Z f − L f Z f V f . (34)
d Z p d t = θ m Z m + θ f Z f V p − k 1 V p ( 2 Z p − Z m − Z f ) . (35)
where
Z k ≡ C k − C k s . (36)
and C k s is the steady state value of C k .
The above equations can be solved simultaneously by using matrix methods where;
d Z _ d t = A _ _ Z _ ; Z _ ( o ) = Z _ o . (37)
Z _ ( s ) = [ I _ _ S − A _ _ ] − 1 Z _ o . (38)
Z _ = [ C m C m s C f C f s C p C p s ] . (39)
Z _ o = [ C m o C m s C f o C f s C p o C p s ] . (40)
I _ = [ 1 0 0 0 1 0 0 0 1 ] . (41)
A _ _ = [ − ( k 1 + θ m ) V m L f V m k 1 V m 0 − ( k 1 + θ f + L f ) V f k 1 V f k 1 + θ m V p k 1 + θ f V p − 2 k 1 V p ] = [ a 11 a 12 a 13 a 21 a 22 a 23 a 31 a 32 a 33 ] . (42)
Note that,
[ I _ _ S − A _ _ ] − 1 = adj ( I _ _ S − A _ _ ) det ( I _ _ S − A _ _ ) . (43)
The characteristic equation is then given by;
s ( s + f 1 ) ( s + f 2 ) = 0. (44)
where
f 1 = 1 2 { ( k 1 + θ m V m ) + ( k 1 + θ f + L f V s ) + ( 2 k 1 V p ) − [ ( k 1 + θ m V m ) − ( k 1 + θ f + L f V f ) ] 2 + 4 k 1 V p ( k 1 V p − L f V f ) } . (45)
and
f 2 = 1 2 { ( k 1 + θ m V m ) + ( k 1 + θ f + L f V s ) + ( 2 k 1 V p ) − [ ( k 1 + θ m V m ) − ( k 1 + θ f + L f V f ) ] 2 + 4 k 1 V p ( k 1 V p − L f V f ) } . (46)
Equations (45) and (46) imply that θ m and θ f are determined if f 1 and f 2 are specified. Two cases for θ m and θ f are possible from Equations (45) and (46):
Case 1:
θ m 1 = x 1 V m − k 1 . (47)
θ f 1 = y 1 V f − k 1 − L f . (48)
Case 2:
θ m 2 = x 2 V m − k 1 . (49)
θ f 2 = y 2 V f − k 1 − L f . (50)
where
2 x 1 = 2 y 2 = ( f 1 + f 2 − β ) { ( f 1 + f 2 − β ) 2 − 2 ( 2 f 1 − β ) ( f 1 + f 2 − β ) − 4 β f 1 + 4 f 1 2 + 2 β L f V f } 1 2 . (51)
2 x 2 = 2 y 1 = ( f 1 + f 2 − β ) { ( f 1 + f 2 − β ) 2 − 2 ( 2 f 1 − β ) ( f 1 + f 2 − β ) − 4 β f 1 + 4 f 1 2 + 2 β L f V f } 1 2 . (52)
Equations (42) to (44) are combined together to give:
[ I _ _ S − A _ _ ] − 1 = [ ( s − a 22 ) ( s − a 33 ) − a 23 a 32 s ( s + f 1 ) ( s + f 2 ) a 12 ( s − a 33 ) + a 13 a 32 s ( s + f 1 ) ( s + f 2 ) a 13 ( s − a 22 ) + a 12 a 23 s ( s + f 1 ) ( s + f 2 ) a 23 a 31 s ( s + f 1 ) ( s + f 2 ) ( s − a 11 ) ( s − a 33 ) − a 13 a 31 s ( s + f 1 ) ( s + f 2 ) a 23 ( s − a 11 ) s ( s + f 1 ) ( s + f 2 ) a 31 ( s − a 22 ) s ( s + f 1 ) ( s + f 2 ) a 32 ( s − a 11 ) + a 12 a 31 s ( s + f 1 ) ( s + f 2 ) ( s − a 11 ) ( s − a 22 ) s ( s + f 1 ) ( s + f 2 ) ] . (53)
The final solutions for three Equations (6) to (8), are written as:
C m ( t ) = C m s + e − f 1 t f 1 − f 2 [ { f 1 + ( k 1 + θ f + L f V f ) + 2 k 1 V p } ( C m o − C m s ) + L f ( C f o − C f s ) + k 1 ( C p o − C p s ) V m ] + e − f 2 t f 2 − f 1 [ { f 2 + ( k 1 + θ f + L f V f ) + 2 k 1 V p } ( C m o − C m s ) + L f ( C f o − C f s ) + k 1 ( C p o − C p s ) V m ] (54)
C f ( t ) = C f s + e − f 1 t f 2 − f 1 [ k 1 V f − ( C f o − C f s ) ( k 1 + θ m V m + 2 k 1 V p + f 1 ) ] − e − f 2 t f 2 − f 1 [ k 1 V f − ( C f o − C f s ) ( k 1 + θ m V m + 2 k 1 V p + f 2 ) ] (55)
C p ( t ) = C p s + e − f 1 t f 2 − f 1 [ ( k 1 + θ m V p ) ( C m o − C m s ) + ( k 1 + θ f V p ) ( C f o − C f s ) + ( k 1 + θ m V m + k 1 + θ f + L f V f − f 1 ) ( C p o − C p s ) ] − e − f 2 t f 2 − f 1 [ ( k 1 + θ m V p ) ( C m o − C m s ) + ( k 1 + θ f V p ) ( C f o − C f s ) + ( k 1 + θ m V m + k 1 + θ f + L f V f − f 2 ) ( C p o − C p s ) ] (56)
All three concentrations are generally expressed by the form:
C ( t ) = C s + G 1 exp ( f 1 t ) + G 2 exp ( f 2 t ) . (57)
where G 1 and G 2 are the functions of unknown parameters: θ m , θ f , δ m , δ f .
This section attempts to summarize the protocol used for the determination of parameters ( k 1 , K m , K f , V ′ max m , V ′ max f ) .
From Equation (17), β is specified. The permeability of “ k 1 ” is then given by;
k 1 = β V p / 2 . (58)
In order to determine the diffusion coefficient of AIB within the human placenta, we have to know the cross sectional area of the placenta. Laga et al. (1973) reported that the surface area of the maternal side is 15.1 m2 and that of the fetal side 12.0 m2. Since both sides are assumed to have the same permeability ( k 1 ) and the problem is approached one dimensionally, the arithmetic average of both areas (14.05 × 10 cm4) was used. Note that the surface area is assumed to be proportional to the wet placental weight ( P w ). The units used hereafter are CGS unit, unless specified. The apparent surface area ( S A ) is then given by;
S A = 14.05 × ( P w 571 ) × 10 4 cm 2 . (59)
where 571 is the wet placental weight statistically reported by Laga et al. (1973). Using the definition of permeability and the apparent thickness of placental diffusion barrier (L), the effective diffusion coefficient (D) is expressed as;
D = k 1 × L / S A = β × V p × L / ( 2 S A ) . (60)
The thickness (L) is assumed to be 13 μ based on the thickness of 10 μ for villous membrane [
D = β ( 0.785 P w ) ( 13 × 10 − 4 ) 2 ( 14.05 × 10 4 ) ( P w 571 ) ( 60 ) = ( 571 ) ( 0.785 ) ( 13 × 10 − 4 ) β 2 ( 14.05 × 10 4 ) ( 60 ) = 3.46 × 10 − 8 β ( cm 2 / s ) (61)
where β is expressed in min−1.
Equation (57) is used to determine the steady state concentration ( C k s ) of each circulation by using the nonlinear regression of experimental data. Stability analysis of Equation (44) by Routh criteria provides that;
f 1 > 0 , f 2 > 0. (62)
From f 1 and f 2 of Equations (45) and (46), respectively, it can be shown;
f 2 ≥ f 1 + β { β − ( 2 L f V f ) } . (63)
In order f 2 to be stable, it is evident from Equation (63) that;
β ≥ ( 2 L f V f ) . (64)
Thus, if the condition of Equations (5)-(69) is satisfied for any experimental data, the parameters of K m , K f , V ′ max m , V ′ max f can be determined.
Although f 1 and f 2 are defined by Equations (45) and (46), respectively, and their constraints are set forth by Equations (62) and (63), the difference between f 1 and f 2 is not known. Thus, f 2 is redefined as;
f 2 = f 1 + ( 1 + h ) β { β − ( 2 L f V f ) } . (65)
where “h” is a slack variable from 0 to 1 with an arbitrary increment of 0.1.
Note that the indirect parameters of δ m and δ f are functions of θ m and θ f , respectively if C m s and C f s are known, as indicated in Equations (31) and (32). θ m and θ f , however, are functions of f 1 and f 2 . as shown in equations from (47) to (52). Therefore, the indirect parameters of δ m , δ f , θ m , θ f are specified if f 1 and f 2 are known. Unfortunately, the magnitudes of f 1 and f 2 are not known analytically. Instead, the relationship between the two is given by Equation (63). However, f 1 and f 2 are parameters given by the exponential terms of Equation (57). Thus, their values must be somewhere between 0.01 and 0.1 to satisfy the variations of concentration time curves during perfusions of up to 5 hours long. Keeping this fact in mind, f 1 was arbitrarily set and then f 2 is fixed under the constraint f Equation (65). Once approximate values of f 1 and f 2 giving the positive physical parameters of δ m , δ f , θ m , and θ f (see Equations (29) and (30)) were found, δ m , δ f , θ m , θ f are assumed to be approximately specified.
Note that such an approach gives the ranges of f 1 and f 2 satisfying the given constraints, rather than providing unique values of f 1 and f 2 . Within the resultant ranges of f 1 and f 2 , the experimental data were fitted for sets of values for f 1 and f 2 until the best fit, given by the Student’s t-test between experimental data and values calculated from the numerical integration, was found. This allowed unique values of f 1 and f 2 to be specified as well as the parameters of δ m , δ f , θ m , and θ f . The ultimate parameters of K m , K f , V ′ max m and V ′ max f are determined by the relationship derived from Equations (29) and (30) as;
K m = C m o 2 θ m / δ m . (66)
K f = C f o 2 θ f / δ f . (67)
V ′ max m = ( C m o + K m ) 2 θ m / K m . (68)
V ′ max f = ( C f o + K f ) 2 θ f / K f . (69)
Such results, along with those from the pseudo steady state model, were used to characterize the mechanism of the amino acid uptake in the human placenta, in the absence and presence of ethanol.
Results were obtained from thirty term human placentas out of forty-three placentas.
The level of ethanol was fairly constant in three runs for the ethanol study throughout perfusion even though ethanol was being metabolized by the placenta. This was because the ethanol level (500 - 1000 mg/dL) was high enough so that the ethanol metabolized did not substantially decrease the ethanol concentration. No further measurements of ethanol were attempted because the main interest was in its effect on the transport of AIB at a given level of ethanol. The closeness of the maternal and fetal concentrations support previous observations by others indicating that ethanol is a freely diffusible substance.
Twenty six experimental runs out of thirty nine runs with AIB (5 - 100 mg/l) were used to calculate the placental tissue concentration from an overall AIB mass balance. Thirteen runs were completed in the absence of ethanol and thirteen runs in the presence of ethanol (500 and 1000 mg/dL). As summarized in
In runs in which AIB was added to both the fetal and maternal perfusates, the fetal AIB concentrations always remained higher than the maternal concentrations. In several runs the calculated placental concentration rose above both the maternal and the fetal perfusate concentrations.
In runs in which AIB was present in both perfusates, the AIB concentrations in each perfusate decreased with time, implying that AIB was being transferred to the placental tissue from both the maternal and the fetal sides. Similar results have been observed by others in the isolated human placental lobule [
Placenta Number | Placenta Weight (gm) | Perfusion Time (min) | AIB level (mg/l) | Number of Samples | Concentration Ratio Fetal/Maternal (Mean) | Gradient* |
---|---|---|---|---|---|---|
19 | 359 | 250 | 10, 40 | 13, 13 | - | M → F |
21 | 605 | 60 | 20 | 7 | 1.37 | M ↔ F |
26 | 480 | 140 | 20, 100, 200 | 4, 5, 6 | 1.69, 1.95, 1.44 | M ↔ F |
12 | 620 | 95 | 5, 10, 40 | 6, 6, 8 | 1.19, 1.29, 1.40 | M ↔ F |
23 | 576 | 70 | 100 | 7 | 1.51 | M ↔ F |
11 | 799 | 110 | 5, 10, 40 | 4, 2, 5 | 1.65, 1.49, 1.54 | M ↔ F |
32 | 523 | 285 | 10, 40 | 15, 15 | - | M → F |
33 | 566 | 160 | 10 | 17 | - | M ← F |
37 | 437 | 80 | 10 | 9 | 1.28 | M ↔ F |
24 | 466 | 20 | 100 | 5 | 1.32 | M ↔ F |
27 | 538 | 60 | 20 | 7 | 1.16 | M ↔ F |
31 | 668 | 30 | 100 | 4 | 1.38 | M ↔ F |
39 | 367 | 90 | 10 | 10 | 1.32 | M ↔ F |
Mean ± S.E. | 539 ± 34 | 112 ± 22 | 49 ± 14 | 8 ± 1 | 1.44 ± 0.05 |
*M → F indicates that AIB is added only to the maternal circulations, while M ↔ F shows that AIB is added simultaneously to both maternal and fetal circulations.
and in the isolated guinea pig placental lobule [21 , 27].
The calculated placental tissue concentration ( C p ) is used to determine α and β on the basis of Equation (15), the latter being derived from a pseudo steady state model. As shown in Equation (17) or (58), the permeability ( k 1 ) is calculated from β , which provides the diffusion coefficient of AIB within the human placenta. Seventeen experimental runs were used for this purpose: eight runs in the absence of ethanol and nine runs in the presence of ethanol. The results are represented in
Since α and β were specified in the previous section, the net active transport rate ( Y m + Y f ) is derived as;
Placenta Number | Placenta Weight (gm) | Perfusion Time (min) | AIB level (mg/l) | Ethanol level (mg/dL) | Number of Samples | Concentration Ratio Fetal/Maternal (Mean) | Gradient* |
---|---|---|---|---|---|---|---|
13 | 550 | 180 | 5, 10, 40 | 500 | 7, 9, 21 | 0.82, 0.96, 1.17 | M ↔ F |
22 | 635 | 180 | 20, 100 | 1000 | 8, 11 | 1.26, 1.37, 1.31 | M ↔ F |
23 | 576 | 90 | 100 | 1000 | 9 | 1.31 | M ↔ F |
24 | 466 | 60 | 150 | 1000 | 7 | 2.08 | M ↔ F |
27 | 538 | 20 | 20 | 1000 | 5 | 1.22 | M ↔ F |
28 | 590 | 30 | 20 | 1000 | 7 | 0.84 | M ↔ F |
29 | 610 | 40 | 20 | 500 | 8 | 0.95 | M ↔ F |
30 | 420 | 30 | 100 | 1000 | 6 | 0.57 | M ↔ F |
31 | 668 | 38 | 100 | 1000 | 5 | 1.33 | M ↔ F |
34 | 476,516 | 50 | 10 | 1000 | 6 | 1.38 | M ↔ F |
35 | 516 | 185 | 10, 40, 100 | 1000 | 8, 8, 4 | 1.31, 1.32, 1.26 | M ↔ F |
36 | 447 | 50 | 10 | 1000 | 6 | 1.32 | M ↔ F |
39 | 367 | 80 | 10 | 1000 | 9 | 1.13 | M ↔ F |
Mean ± S.E. | 528 ± 25 | 80 ± 17 | 45 ± 10 | - | 8 ± 1 | 1.20 ± 0.08 | - |
**P value | 0.790 | 0.260 | 0.810 | - | 1000 | 0.016 | - |
*M → F indicates that AIB is added only to the maternal circulations, while M ↔ F shows that AIB is added simultaneously to both of maternal and fetal circulations. **P value was determined by the Student t-test for unpaired data with equal population variances.
( Y m + Y f ) = β V p { α − ( C m + C f ) / 2 } . (70)
where C m and C f are the average concentrations in maternal and fetal circulations, respectively. By Equation (19)
U ′ p = U ′ a − U ′ d . (71)
where U ′ indicates the first derivative of uptake with respect to time and thus represents an uptake rate. From Equation (50),
U ′ p = d U P / d t = { β V p ( α − C p o ) } exp ( − β t ) . (72)
From definition,
U ′ a = Y m + Y f . (73)
Substituting Equations (72) and (73) into (71) gives;
U ′ d = β V p { C p − ( C m + C f ) / 2 } . (74)
Placental Number | AIB level (mg/l) | α (dpm/ml) | β (ml/min) | Specific Activity (mg/dpm) 1 × 10−5 | Permeability k1 (ml/min) | Diffusion Coefficient (cm2/sec) 1 × 10−9 | Ym + Yf (mg/hr/kg placenta) |
---|---|---|---|---|---|---|---|
CONTROL (n = 8) | |||||||
11 | 40 | 1264 | 0.0387 | 2.5 | 12.2 | 1.3 | - |
12 | 10 | 624 | 0.2912 | 2.3 | 70.9 | 10.1 | 86 |
21 | 20 | 4607 | 0.0578 | 0.8 | 13.7 | 2.0 | 60 |
23 | 100 | 1670 | 0.0203 | 17.6 | 4.6 | 0.7 | 186 |
26 | 20 | 439 | 0.0748 | 3.5 | 14.1 | 2.6 | 12 |
26 | 100 | 1597 | 0.1291 | 4.3 | 24.3 | 4.5 | 157 |
37 | 10 | 1223 | 0.0293 | 1.1 | 5.0 | 2.9 | 6 |
39 | 10 | 7247 | 0.0161 | 0.6 | 2.3 | 5.6 | 25 |
Mean ± S.E. | 39 ± 14 | 2334 ± 836 | 0.0822 ± 0.0330 | 4.3 ± 2.3 | 18.4 ± 7.9 | 3.7 ± 1.1 | - |
Placental Number | AIB level (mg/l) | α (dpm/ml) | β (ml/min) | Specific Activity (mg/dpm) 1 × 10−5 | Permeability k1 (ml/min) | Diffusion Coefficient (cm2/sec) 1 × 10−9 | Ym + Yf (mg/hr/kg placenta) |
---|---|---|---|---|---|---|---|
ETHANOL (n = 9) | |||||||
22 | 20 | 2624 | 0.01028 | 1.3 | 25.6 | 3.5 | 64 |
22 | 100 | 5242 | 0.0137 | 3.1 | 3.4 | 0.5 | 43 |
23 | 100 | 1778 | 0.1452 | 12.4 | 32.8 | 5.0 | 909 |
28 | 20 | 253 | 0.1220 | 9.4 | 28.2 | 4.2 | 45 |
31 | 100 | 26680 | 0.0407 | 0.9 | 10.7 | 1.4 | 321 |
34 | 10 | 3402 | 0.0849 | 0.6 | 15.9 | 2.9 | 40 |
35 | 10 | 2443 | 0.0229 | 0.6 | 4.6 | 0.8 | 7 |
35 | 40 | 6531 | 0.0311 | 1.0 | 6.3 | 1.1 | 40 |
36 | 10 | 2962 | 0.0405 | 1.1 | 7.1 | 1.4 | 45 |
Mean ± S.E. | 46 ± 14 | 5768 ± 2685 | 0.0671 ± 0.0160 | 3.4 ± 1.5 | 15.0 ± 3.7 | 2.3 ± 0.5 | - |
P value | 0.73 | 0.26 | 0.67 | 0.72 | 0.25 | 0.25 | - |
Note that U ′ d > 0 indicates that the net diffusive transport occurs from placental tissue to perfusates, and that U ′ d < 0 indicates that the transport occurs in the opposite direction.
The relative contribution of diffusive transport, R C d , to the placental uptake can be given by taking the absolute value of U ′ d as | U ′ d | to be free from the direction of transport. Then,
R C d ( % ) = 100 × | U ′ d | / ( U ′ a + | U ′ d | ) . (75)
Thus, the relative contribution of active transport, R C a , to the placental uptake is given by;
R C a ( % ) = 100 − R C a ( % ) . (76)
The results are represented in
Placenta Number | AIB level (mg/l) | Relative Contribution (%) | ||
---|---|---|---|---|
Diffusion *(Mean ± S.D.) | Active Transport | |||
CONTROL (n = 7) | ||||
12 | 10 | 43 ± 13 | 57 | |
21 | 20 | 37 ± 15 | 63 | |
23 | 100 | 24 ± 13 | 76 | |
26 | 20 | 71 ± 11 | 29 | |
26 | 100 | 58 ± 10 | 42 | |
39 | 10 | 26 ± 13 | 72 | |
37 | 10 | 8 ± 6 | 92 | |
**Mean ± S.E. | 39 ± 16 | 38 ± 8 | 62 | |
ETHANOL (n = 9) | ||||
22 | 20 | 45 ± 15 | 55 | |
22 | 100 | 26 ± 14 | 74 | |
23 | 100 | 47 ± 7 | 53 | |
35 | 10 | 25 ± 4 | 76 | |
35 | 40 | 32 ± 13 | 68 | |
28 | 20 | 42 ± 18 | 58 | |
31 | 100 | 28 ± 14 | 72 | |
34 | 10 | 41 ± 11 | 59 | |
36 | 1 | 31 ± 13 | 69 | |
Mean ± S.E. | 46 ± 14 | 35 ± 3 | 65 | |
P value | 0.75 | 0.71 | 0.70 | |
*: Averaged over samples of the run period. **: Averaged over the number of run.
tissue.
Thirteen experimental runs were used to determine the individual rates of active transport as well as diffusion from both the maternal and fetal sides, from the results of the relative contribution of transport processes (
d U m / d t = Y m − K D m . (77)
d U f / d t = Y f − K D f . (78)
d U p / d t = ( Y m + Y f ) − ( K D m + K D f ) . (79)
where
K D m = k 1 ( C p − C m ) . (80)
K D f = k 1 ( C p − C f ) . (81)
K D m and K D f represent the maternal and fetal diffusive contributions, respectively, and Y m and Y f are assumed constant. Since C m and C f are relatively constant and C p changes markedly, K D m and K D f are not constant during the course of a perfusion at a given perfusate AIB concentration. The average values, over the course of the experiment at a given AIB level, were added to the values of ( d U m / d t ) and ( d U f / d t ) to obtain separate values of Y m and Y f , respectively. Once Y f is specified, Y m is determined from the known value of ( Y m + Y f ) , These relationships are based on average rates of active transport, diffusive transport, and net uptake. The ratios of the average values of K D m and K D f were also calculated for both the control and the ethanol groups. The calculated Y m + Y f in
A range of possible values for K m , K f , V ′ max m and V ′ max f is first determined using the linearized model. Using this range of each parameter, a direct search is made to obtain the values of K m , K f , V ′ max m and V ′ max f which best fit the experimental data to the predictions obtained by the numerical integration of Equations (6) to (8). Values of the parameters obtained by this procedure for eight experimental runs are given in
Placenta Number | AIB level (mg/l) | Percent Maternal Uptake (Mean ± S. D.) | Uptake Ratio (Um/Uf) *(Mean ± S. D.) |
---|---|---|---|
CONTROL (n = 6) | |||
21 | 20 | 83 ± 4 | 4.2 ± 1.7 |
23 | 100 | 48 ± 43 | 3.7 ± 6.5 |
26 | 20 | 58 ± 3 | 1.4 ± 0.5 |
26 | 100 | 61 ± 4 | 1.6 ± 0.3 |
26 | 200 | 61 ± 5 | 1.6 ± 0.3 |
27 | 10 | 77 ± 2 | 3.3 ± 0.2 |
**Mean ± S. E. | 75 ± 30 | 65 ± 5 | 2.6 ± 0.5 |
ETHANOL (n = 10) | |||
13 | 40 | 76 ± 5 | 3.3 ± 1.0 |
22 | 20 | 75 ± 4 | 3.1 ± 0.8 |
22 | 100 | 68 ± 4 | 2.2 ± 0.4 |
23 | 100 | 61 ± 8 | 3.3 ± 5.2 |
28 | 20 | 73 ± 9 | 3.0 ± 1.0 |
31 | 100 | 66 ± 9 | 2.1 ± 0.8 |
34 | 10 | 59 ± 29 | 2.1 ± 1.3 |
35 | 10 | 76 ± 9 | 3.8 ± 2.0 |
35 | 40 | 55 ± 8 | 1.3 ± 0.4 |
36 | 10 | 49 ± 2 | 1.0 ± 0.1 |
Mean ± S. E. | 45 ± 12 | 55 ± 3 | 2.5 ± 0.3 |
P value | 0.30 | 0.84 | 0.84 |
*: Averaged over samples of the run period. **: Averaged over the number of runs.
These results imply that the placental uptake from the maternal side governs the net placental uptake of AIB regardless of ethanol presence. Furthermore any reduction in overall AIB uptake by ethanol must be the result of reductions in the uptakes from both the maternal and fetal sides. These results are consistent with those of Van Dijk and Van Krell (1978), who suggested that AIB uptake in the perfused guinea pig placenta takes place from both sides but preferentially from the maternal circulation, and Wier et al. (1982), who reported an abstract suggesting that 70% of the placental AIB originates from the maternal circulation after 4 hours of perfusion using the isolated human placental lobule. The preferential maternal transfer is also observed in the experiments using the single addition technique (
In other words, 51% of the amount added to the maternal side is retained by the placental tissue, while 79% of the amount added to the fetal side is retained by the placental tissue. Secondly, the% maternal to fetal transfer (M → F) is probably enhanced by the larger placental tissue uptake from the maternal side. On the other hand, the% fetal to maternal transfer (F → M) is not so large since the uptake rate from the fetal side is smaller. These results support the previous qualitative postulation by Curet (1971) that amino acids, once they leave the maternal circulation, do not immediately cross the placental tissue to be taken up by the fetal circulation. Rather, there is an intermediate stage where amino acids are stored in the placental tissue for a transient period of time, after which they are released into the fetal circulation.
A number of studies have demonstrated that the movement of amino acids across the placenta s bidirectional [20 , 23]. In particular, Wier et al. [
Van Dijk and Van Kreel [
The relative magnitude of the contribution of active and diffusive processes in the placenta is not apparent from the literature, although Kelman and Sikov (1983) attempted to clarify the relative roles of active and diffusive movements of AIB across the placenta using rapidly diffusible water and actively transported AIB. They proposed that a relatively large component of AIB uptake is of diffusive origin in the in situ placenta. However, their protocol of using tritiated water along with AIB is based on the assumption that the diffusive process of water is equivalent to that of AIB, which is unlikely to be due to the significant difference of their partition coefficients. Thus, the clearance of water may not represent the diffusive process of AIB. However, if AIB is used along with L-glucose instead of water, the diffusive part of AIB can be represented by the transport of L-glucose which has a similar permeability or diffusion coefficient as AIB. L-glucose has been, in fact, used by Yudilevich and his associates [21 , 22 , 51] to eliminate diffusive processes and to determine the kinetic parameters for placental amino acid uptake in the guinea pig using the paired dilution technique. Total AIB uptake is controlled by an active transport mechanism and a diffusive process, the latter being dependent upon the duration of exposure to AIB and the concentration of AIB used [
As indicated in
In the presence of ethanol, however, the diffusive ratio is increased to 1.43 ± 0.15. Such an altered ratio by ethanol can be due either to increased maternal diffusive transport ( K D m ) or to decreased fetal diffusive transport ( K D f ). There is a possibility of increased K D m , since ethanol increases the maternal fluidity, as shown by Wilson and Hoyumpa [
PARAMETER | MATERNAL | FETAL | ||||
---|---|---|---|---|---|---|
GROUP | K m (kg/l) | V max m (mg/hr/kg placenta) | R2 (%) | K f (kg/l) | V max f (mg/hr/kg placenta) | R2 (%) |
CONTROL (n = 5) | 8.1 | 34.8 | 10.1 | 16.0 | 45.5 | 50.4 |
ETHANOL (n = 8) | 20.4 | 71.9 | 40.9 | 24.8 | 51.8 | 47.9 |
R2 indicates the correlation coefficient from the regression of the reciprocal of active rate with respect to the reciprocal of AIB concentration.
The ratios of the active transport to diffusive transport from both the maternal and fetal sides also seem to be increased by ethanol, but the ratio from the fetal side seems to be relatively more, increased. This result in comparison with the above result for ( K D m / K D f ) , suggesting that maternal diffusive transport is also reduced by ethanol, but that its extent of inhibition is less than that of the fetal diffusive process. Therefore, the diffusive processes from both circulations may be reduced by ethanol, with the fetal side relatively more inhibited.
1) The overall mass balance over the perfusion system can be used to calculate the time course of the placental tissue AIB concentration in the whole human placenta. The latter is consistent with the directly measured tissue concentration at the end of perfusion as long as the duration of perfusion is long enough (>1 hr) and no maternal perfusate is lost toward the outside of the system. The percent error (mean ± standard error) between the calculated and measured placental tissue concentrations is 3% ± 12%.
2) The effective diffusion coefficients of AIB within the human placenta are 3.7 × 10−9 cm2/s (the control group) and 2.3 × 10−9 cm2/s (the ethanol group), with no statistical difference (P = 0.25). The results are comparable to the published data of L-glucose, which has a partition coefficient similar to AIB.
3) The overall placental uptake is higher than that from the fetal circulation, regardless of the presence of ethanol. The ratios of maternal to fetal uptake are 2.6 ± 0.5 for six control runs and 2.5 ± 0.3 for ten ethanol runs, with no statistical difference (P = 0.84).
4) The transfer direction from the maternal to the fetal circulation (49% transferred) is preferred over that from the fetal to the maternal movement (21% transferred). It appears that the placental tissue plays a role of mediator to maintain a higher fetal concentration than the maternal side by either enhancing the maternal to fetal transfer or impairing the fetal to maternal transfer.
5) The relative contribution of the diffusive transport to the net placental uptake of AIB from both the maternal and fetal circulations is less than that of the active transport mechanism for both groups: control (38%) and ethanol (35%) for the dual addition experiments studied here. The results suggest that the active transport mechanism governs the placental uptake of AIB during the initial transient period, while the contributions by active and diffusive processes approach each other at steady state.
6) The placental uptake of AIB from the maternal side by diffusive transport is about the same as the uptake by diffusive transport from the fetal circulation in the absence of ethanol. However, the ratio of the maternal to the fetal diffusive uptakes is much higher (1.43) in the presence of ethanol. The results suggest that diffusive transport on the fetal side is more inhibited by ethanol than is diffusive transport on the maternal side. The result also suggests that the permeability of AIB on the fetal side may be less than that on the maternal side.
7) The placental uptake of AIB from the maternal side by active transport is higher than that from the fetal side for both groups: control (1.3) and ethanol (1.5).
8) The present report appears to be the first wherein individual kinetic analyses for the maternal and fetal AIB active transport in the human placenta have been completed. The results available from the pseudo steady state and the unsteady state approaches, based on the conceptual model of dual active transport, indicate that the active transport mechanisms on both sides are inhibited in the presence of ethanol.
9) An overall effect of ethanol on AIB transport in the perfused human placenta is to significantly (P = 0.016) reduce the ratio of the fetal to maternal perfusate concentrations.
10) In summary, acute in vitro ethanol administration in the perfused whole human placenta reduces both the diffusive and active transport mechanisms of AIB. The extent of inhibition seems to be larger on the fetal side.
The authors express sincere appreciations to Dr. Gerald B. Gordon for the ultrastructural study, Dr. Douglas C. Kuhn for constructive suggestion, Dr. Michael S. Baggish and Dr. Robert E. L. Nesbitt for providing facilities of the placental perfusion in the Department of Obstetrics and Gynecology, Upstate Medical Center, State University of New York, USA.
The authors declare no conflicts of interest regarding the publication of this paper.