The neuronal AP model was programmed using Python operating language and the module NumPy (Enthought). The sodium current was modeled following the formulas of Hodgkin and Huxley (1952; Eq. 10), with 0 mV defined as an absolute value, instead of the resting membrane potential.

where I_Na is the fast sodium current, G_Na is the maximal sodium conductance value, m is the conductance gate, h is the FI gate, j is the slow inactivation gate, V is the membrane potential, and E_Na is the Nernst potential for sodium.

The conductance (m) gate and FI (h) gate steady-states (see Eqs A4 and A5 in Appendix) were fit to the experimental data using Eqs 2 and 5, respectively. The steady-state of the slow inactivation (j) gate (see Eq. A7 in Appendix) was fit to Eq. 6. Activation time constants were chosen to be constant following previously published reports (Spampanato et al., 2001, 2003). The time constant vs. voltage curve of FI (see Eq. A6 in Appendix) was fit to an asymmetric inverse hyperbolic cosine function (Eq. 11).

where τ is the time constant, T_max is the maximum time constant, V_1/2 is the membrane potential at which the maximal time constant occurs, and k₁ and k₂ are the slopes of the left and right halves of the curve.

Slow inactivation time constants (see Eq. A8 in Appendix) were fit in the same method as (Spampanato et al., 2001, 2003) with a Gaussian distribution (Eq. 12).

where τ is the time constant, T_max is the maximum time constant, V_1/2 is the membrane potential at which the maximal time constant occurs, and k₁ is the slope factor of the curve.

A non-inactivating potassium current (Eqs A9–A13 in Appendix) and maximal conductance, Nernst potential, and cell capacitance parameters were used based on previously published formulas (Yuen and Durand, 1991; Spampanato et al., 2001, 2003). Stimulation protocols were done with a continuous stimulation over 105 ms at amplitudes ranging from −1 to −20 pA/pF.

The original ten Tusscher model (Ten Tusscher et al., 2004) was programmed into Python code making use of the module NumPy (Enthought). The code was then updated to include calcium current and slow delayed potassium current equations (Ten Tusscher and Panfilov, 2006). A late persistent sodium current was added (Eqs A24–A29 in Appendix; Hund and Rudy, 2004). The maximal sodium conductance value was replaced with the Luo–Rudy passive model value to better reflect our experimental data (Luo and Rudy, 1991). The slow delayed rectifier potassium conductance (G_Ks; Eq. A30 in Appendix) was changed to incorporate the role of internal calcium concentrations on gKs (Terrenoire et al., 2005). The late sodium maximal conductance value was changed to reflect the data collected by (Zygmunt et al., 2001). The sodium current was modeled using Eq. 10. Our sodium channel conductance steady-states at both pH 7.4 and pH 6.0 (Eq. A14 in Appendix) were fit with Eq. 2 with the conductance value multiplied by the proton block in the pH 6.0 model. FI steady-state curves at both pH values (Eq. A18 in Appendix) were fit with Eq. 5. Slow inactivation steady-states curves at both pH values (Eq. A20 in Appendix) were fit with Eq. 6. Time constants of FI at both pH values (Eq. A19 in Appendix) were fit to an asymmetric inverse hyperbolic cosine function, Eq. 11. Activation and slow inactivation time constants (Eqs A15–A17 and A21–A23 in Appendix) were as described by the ten Tusscher model. The sodium channel parameters were then Q10 adjusted following the methods used in the model (Ten Tusscher and Panfilov, 2003) which used the work of Nagatomo et al. (1998). The simulation was run as an endocardial ventricular myocyte with a 1-ms stimulus pulse of amplitude −60 pA/pF. The stimulus protocol had a cycle length of 400 ms for the first 15 APs, 350 ms for the next 15, 325 ms for the next 10, and 300 ms for all subsequent APs. This was done to step the stimulus rate up to 3.33 Hz gradually and allow AP shortening. AP parameters were measured at both 2.5 Hz (150 beats per minute) and 3.33 Hz (200 beats per minute) to study the AP properties that acidosis of the cardiac voltage-gated sodium channel modulates at high heart rates. Measurements of APD were obtained from the time of stimulus to the time at which the membrane potential reaches a value of −70 mV. Maximal depolarization rise rates were measured as the maximum slope between two sequential membrane potentials after the stimulus current was ended. Equations modified from the original Tusscher model are listed in the Appendix.

All statistical values, both in the text and in the figures, are given as means ± standard error of the mean (SEM). Statistical differences were derived from Student’s t-test using the Instat software package (GraphPad Software, Inc., San Diego, CA, USA).

Previous studies demonstrated that acidic pH decreases the amplitude of macroscopic sodium currents. Figures 1A,D,G show typical families of Na_V1.2, Na_V1.4, and Na_V1.5 recorded at control pH 7.4 in response to a depolarizing pulse protocol shown in insets of Figure 1. The current amplitude decreased in all three channel isoforms when pH was lowered to 6.0 (Figure 1, compare Figures 1A,Ai,D,Di,G,Gi). Amplitudes decreased by 32 ± 5, 35 ± 4.3, and 53 ± 7% for Na_V1.2, Na_V1.4, and Na_V1.5, respectively. In contrast to Na_V1.2 and Na_V1.4, the decay of macroscopic currents in Na_V1.5 at pH 6.0 was slower (denoted with the arrow in Figure 1Gi) compared to the control family of currents at pH 7.4 (Figure 1G). These results suggest that low pH alters properties of open-state inactivation.

We examined the effects of low pH on activation in Na_V1.2, Na_V1.4, and Na_V1.5. Data in Figures 1B,E,H represent normalized control maximum conductance derived from I(V) relationships at pH 7.4 (filled circles) and pH 6.0 (open circles). Normalized conductance was plotted as a function of membrane potential and fit with the Boltzmann function (Eq. 1, Materials and Methods) to obtain values for V_1/2 and apparent valence (z). The G(V) parameters we measured are shown in Table 1. At pH 6.0 the apparent valence of activation in Na_V1.5 was significantly increased (p < 0.05). The V_1/2 of activation in Na_V1.5 was unaffected by low pH. In contrast, neither apparent valence nor the V_1/2 in Na_V1.2 and Na_V1.4 were altered by low pH (p > 0.05, Figures 1B,E, respectively).

To quantify the effects of low pH on voltage-dependent steady-state channel availability in fast-inactivated state, we compared the apparent valence (z) and V_1/2 from Boltzmann fits (Eq. 5, Materials and Methods) to steady-state FI data for Na_V1.2 (Figure 1B), Na_V1.4 (Figure 1E), and Na_V1.5 (Figure 1H) at pH 7.4 (filled triangles) and at pH 6.0 (open triangles). These data represent averaged, normalized current amplitudes obtained with a test pulse to 0 mV following a 500-ms prepulse (pulse protocol is shown in insets). Normalized current amplitudes were plotted as a function of prepulse potential. At pH 6.0 the apparent valence of steady-state FI in NaV1.2 was reduced from that at pH 7.4 to the value measured at pH 6.0 (n = 11). The V_1/2 of inactivation was not affected by low pH (Table 2). Low pH had no effect on steady-state FI in Na_V1.4 (Table 2). In Na_V1.5 the apparent valence was not altered at pH 6.0, but the V_1/2 was depolarized compared to the V_1/2 at pH 7.4.

Changes in activation and steady-state inactivation slope and V_1/2 may alter the area of overlap between activation and steady-state FI curves, known as “window current.” We studied this possibility by comparing this area at both pH 7.4 and 6.0 for Na_V1.2, Na_V1.4, and Na_V1.5. Figures 1C,F,I shows window current at pH 7.4 (solid line) and at pH 6.0 (dotted line) of Na_V1.2, Na_V1.4, and Na_V1.5, respectively. Data in these graphs were converted to percents (Wang et al., 1996) and plotted as a function of membrane potential. To compare the effects of pH on window currents, window currents were analyzed as described in Materials and Methods to find the area and peak position relative to membrane potential on the horizontal axis. Low pH had no significant effect on window currents in Na_V1.2 (Figure 1C, p > 0.05). Window current area in Na_V1.4 (Figure 1E) was reduced at pH 6.0 by 47 ± 4.5% (p < 0.05), however peak position was not changed: −51 ± 1.3 mV at pH 7.4 vs. −49 ± 1.0 mV at pH 6.0. Window current area in Na_V1.5 was not significantly altered by low pH, but the peak was shifted from −60.4 ± 0.7 mV (pH 7.4) to −53 ± 0.8 mV (1I, p < 0.05). The latter finding indicates a possible destabilization of FI gating in Na_V1.5 at low pH.

As shown above, the decay of Na_V1.5 macroscopic currents was decelerated at pH 6.0. We asked whether this effect is specific to NaV1.5. Figure 2 compares the effects of pH on open-state FI (FI) in Na_V1.2, Na_V1.4, and Na_V1.5. Data in Figures 2A–C represent time constants of open-state FI derived from exponential fits to decay of macroscopic current recorded from Na_V1.2 (Figures 2Ai,Aii), Na_V1.4 (Figures 2Bi,ii), Na_V1.5 (Figure 2Ci,ii) at pH 7.4 and pH 6.0. Pulse protocols are shown in Figures 2Aii,Bii,Cii insets. Time constants were plotted as a function of membrane potential and fitted with single exponential for visual guidance. Figure 2A shows that time course of open-state inactivation in Na_V1.2 at pH 7.4 (filled circles) is statistically identical (p > 0.05) to that at pH 6.0 (open circles). Similarly to Na_V1.2, the open-state inactivation in Na_V1.4 (Figure 2B) at pH 7.4 (filled circles) was not affected (p > 0.05) by low pH (open circles). However, the time course of open-state inactivation in Na_V1.5 at pH 6.0 (Figure 2C, open circles) was significantly slower than that recorded at pH 7.4 (Figure 2C, filled circles, asterisks denote p < 0.05), also see Figures 2Ci,ii arrow. Thus, data in Figure 2 suggest that deceleration of rate of open-state FI due to low pH is specific to Na_V1.5, and is not seen in Na_V1.2 or Na_V1.4.

We studied effects of pH on the time course of recovery from fast-inactivated state (Figure 3), onset to FI (Figure 4), and consequently, the τ(V) dependence of FI (Figure 5). The rate of recovery from FI was studied using a double-pulse protocol (shown in Figure 3, inset). The fraction of recovered channels was measured from the peak current during a 0-mV test pulse. The current amplitude following recovery was normalized to the current amplitude during a pulse to 0 mV from −130 mV, a voltage at which all channels should be available (not inactivated). Recovery from FI in Na_V1.2, Na_V1.4, and Na_V1.5 was recorded with interpulse voltages from −120 to −80 mV. The rate of recovery from fast inactivation was greater in all three channel isoforms at low pH. Figure 3 shows the time course of recovery from fast inactivation at pH 7.4 (filled circles) and at pH 6.0 (open circles) in Na_V1.2 (Figure 3A), Na_V1.4 (Figure 3B), and Na_V1.5 (Figure 3C). Data represent averaged and normalized current amplitudes recorded in response to test pulse following a −80-mV interpulse (see pulse protocol diagram in Figure 3 inset), plotted as a function of interpulse duration (ms). For clarity, recovery data for other interpulse voltages are not shown. Solid lines are single exponential fits (Eq. 3), used to extract time constants to compare recovery at pH 7.4 and pH 6.0. We also found that more Na_V1.4 channels are available for recovery at the beginning (t = 0) of interpulse (Figure 3B, filled circles, arrow) at pH = 7.4 compared to pH = 6.0 (open circles, Figure 3B).

The effects of low pH on the rate of FI onset (Figure 4) were studied by measuring the test pulse current amplitude after a 0- to 500-ms prepulse of defined voltage (see protocol diagrams in Figures 4A,B). In response to increasing duration of prepulse, the fraction of inactivated channels, assayed with 0 mV test pulse is increased, as shown in Figures 4A,B. Data in Figure 4 are normalized and averaged test pulse currents plotted as a function of prepulse duration. The rate of onset (given as a time constant) and steady-state fraction of inactivated channels (given as an asymptote) was quantified by fitting data with single exponential (Eq. 3). Onset of FI in Na_V1.4 at pH 7.4 was not different (p < 0.05) from that at pH 6.0 at prepulse potentials of −70, −60, −50, and −40 mV (data not shown). However, the onset to FI in Na_V1.2 (Figure 4A) and in Na_V1.5 (Figure 4B) was differentially affected by low pH. A direct comparison of pH effects on FI onset between Na_V1.2 and in Na_V1.5 at pH = 7.4 (filled circles) and at pH = 6.0 (open circles) was confounded by an isoform- and pH-dependent difference in the peak of the τ(V) curve (shown in Figure 5). The steady-state fraction of inactivated channels in Na_V1.2, Na_V1.4, and Na_V1.5 was not altered by low pH (p > 0.05, data not shown).

Different voltage protocols were used in Na_V1.2 and Na_V1.5 to assess the effects of pH on the onset of fast inactivation, as shown in Figure 4, because of a difference in τ(V) relationships between these two isoforms. As shown in Figure 5, the τ(V) for Na_V1.2 is depolarized relative to Na_V1.5. Had we compared −60 mV for both isoforms, we would have measured recovery from fast inactivation in Na_V1.2 and onset of fast inactivation in Na_V1.5. We chose to compare −30 mV in Na_V1.2 with −60 mV in Na_V1.5 because of their similar positions relative to the peak of their respective τ(V) curves, as seen in Figure 5.

In Figure 5, the averaged time constants of FI recovery (circles), closed-state FI onset (squares), and open-state FI onset (triangles) are plotted as a function membrane (interpulse and prepulse) potential at pH 7.4 (solid symbols) and pH 6.0 (open symbols). The averaged time constants were fit using a two-state (not inactivated ↔ inactivated) Eyring first-order reaction model (solid lines, Eqs 7–9, Materials and Methods). The coefficients of fits to FI time constants are summarized in Table 3. Low pH strongly affects the τ(V) in Na_V1.2 and Na_V1.5 by accelerating rate of recovery from FI, slowing rate entry to FI and producing depolarizing shift in maximum of τ(V) curve. In contrast, effects of low pH on τ(V) in Na_V1.4 are limited to an increase in the rate of recovery from FI (Figure 5B).

We compared the effects of low pH on steady-state slow inactivation (SS-SI) in Na_V1.2, Na_V1.4, and Na_V1.5 (Figure 6). SS-SI was measured using a 60-s prepulse followed by a 20-ms, −150 mV FI recovery pulse immediately before the 0-mV test. After the test pulse, channels were hyperpolarized to −130 mV for 30 s before every prepulse to completely recover channels from both fast and slow inactivation (Featherstone et al., 1996). Data points represent averaged and normalized amplitudes of currents recorded during test pulse (see pulse protocol diagram in Figure 6 inset). Figure 6A shows SS-SI in Na_V1.2 at pH 7.4 (filled circles) and pH 6.0 (open circles). Figure 6B shows SS-SI in Na_V1.5 at pH 7.4 (filled squares) and at pH 6.0 (open squares). Data are plotted as a function of prepulse potential. Data sets were fitted with modified Boltzmann function (Figure 6, solid lines, Eq. 6, Materials and Methods) to obtain values for maximum probability, apparent valence (z), and V_1/2, summarized in Table 4. Data in Figure 6 were closely matched by asymptotic values of exponential fits to the data in Figures 7A,C at corresponding voltages (−50 mV).

Our results revealed no significant differences in properties of SS-SI in Na_V1.4 recorded at pH 7.4 and at pH 6.4 (data not shown). However, low pH produced shifts in V_1/2: hyperpolarizing for Na_V1.2 and depolarizing for Na_V1.5 (see Table 4).

Figures 7A,C show time course of onset of SI in Na_V1.2 at pH 7.4 (filled circles) and at pH 6.0 (open circles) and in Na_V1.5 at pH 7.4 (filled squares) and at pH 6.0 (open squires), respectively. The onset of SI was assessed by recording peak currents during the test pulse preceded by −50 mV prepulse of varied duration (0–64 s). As with the pulse protocol for steady-state SI (Figure 6), a 20-ms, −130 mV pulse immediately prior to a test pulse was used to recover channels from accumulated FI. After the test pulse, channels were hyperpolarized to −130 mV for 30 s before every prepulse to completely recover channels from both fast and SI. The pulse protocol is shown below Figure 7C. Data points in Figures 7A,C are averaged and normalized amplitudes of peak currents recorded in response to a test pulse (as described above). The time course of SI onset was fit with double exponential (solid lines, Eq. 4, Materials and Methods) and time constants were extracted. Parameters, derived from the double exponential fits are summarized in Table 5. Asymptotic values of onset to SI at both pH values were added Figure 6 to verify SS-SI data. In Na_V1.2, at pH 6.0 the asymptotic value of onset of SI was significantly decreased. Also, at low pH the slow time constant (τ₂) was significantly smaller at pH 6.0 compared to pH 7.4. In contrast, the asymptotic value of onset of SI in Na_V1.5 was significantly increased at pH 6.0 compared with pH 7.4 (p < 0.05, n = 7), and the slow component (τ₂) of SI onset was significantly smaller at pH 6.0 compared to pH 7.4 at pH 7.4 (p < 0.05, n = 7).

Figures 7B,D show time course of recovery from SI in Na_V1.2 at pH 7.4 (filled circles) and at pH 6.0 (open circles) and in Na_V1.5 at pH 7.4 (filled squares) and at pH 6.0 (open squares), respectively. The recovery from SI was measured as follows: channels were inactivated with 60 s prepulse at 0 mV, and then recovered from inactivation with a −110-mV interpulse of variable duration (0–64 s, see Materials and Methods for details about the interpulse duration protocol). A short pulse of 20 ms, at −130 mV immediately prior to the test pulse was used to recover channels from FI. The fraction of channels recovered from SI was assessed with a 0-mV test pulse. The pulse protocol is shown below Figure 7D. Currents, recorded during the test pulse were normalized, averaged, and plotted vs. interpulse duration. The time course of recovery from SI in Na_V1.2 was fitted with a double exponential (Eq. 4, Materials and Methods) to obtain time constants and asymptotic values, summarized in Table 5. Low pH did not significantly affect the faster component (τ₁) of recovery from SI in Na_V1.2. However, the slower time constant (τ₂) of recovery from SI was significantly decreased at pH 6.0 (p < 0.05, n = 6, Figure 7B). The asymptotic value of time course from recovery from SI in NaV1.2 at pH 6.0 was not different (p > 0.05) from that at pH 7.4.

Figure 7D shows time course of recovery from SI in NaV1.5 at pH 7.4 (filled squares) and at pH 6.0 (open squares). Comparing the time constants extracted from double exponential fits revealed no significant (p > 0.05) effect of low pH on either on τ₁ or τ₂. However, we found that, at pH 6.0, more NaV1.5 channels are available for recovery at the beginning (t = 0) of interpulse (Figure 7D, open squares, arrow) as compared to pH 7.4 (Figure 7C, filled squares). The asymptotic values for recovery from SI in Na_V1.5 at pH 6.0 were not different (p > 0.05) from those at pH 7.4 (Table 5).

Our experiments revealed no significant effects of low pH kinetics of SI in Na_V1.4 channels (data not shown).

To further investigate the effects of low pH on inactivation in Na_V1.2 and Na_V1.5, we compared use-dependent current reduction at pH 7.4 and pH 6.0. The frequency of pulse stimulation for each channel isoform was chosen to emulate its tissue-specific activity prior to/during an ischemic event, such as epileptic episode or stroke (Kjekshus, 1986; Adeli et al., 2003). Figure 8A shows use-dependent inactivation (UDI) in Na_V1.2 at pH 7.4 (filled circles) and at pH 6.0 (open circles). Peak current amplitudes, recorded during a series of 1000, 20 ms test pulses to 0 mV are plotted as a function of pulse number. The interval between adjacent pulses was 1 ms, holding potential was −60 mV to emulate neuronal resting potential in vivo. The resulting frequency was approximately 45 ± 5 Hz, which roughly corresponds to frequency of AP firing during epileptic episode (Adeli et al., 2003). Peak currents were normalized to the peak amplitude of the first current record of the series and fit with a double exponential function to determine time constants, τ₁ and τ₂, and steady-state fraction of inactivated channels (asymptote). UDI parameters are summarized in Table 6.

At pH 7.4 (Figure 8A, filled circles) the asymptote of UDI in Na_V1.2 was significantly (p < 0.05) decreased compared to that at pH 6.0 (Figure 8A, open circles). Also, acidification accelerated the τ₂ of UDI in Na_V1.2 (Figure 8Ai, open histogram), Table 6. Data shown in Figures 8B,Bi indicate that both time course and maximum probability of UDI in Na_V1.4 at pH 7.4 (filled circles and histograms) were statistically similar (p > 0.05) to those at pH 6.0 (open circles and histograms), Table 6. In Na_V1.5 the effects of low pH on UDI were essentially reversed as compared to Na_V1.2. At pH 7.4 the asymptote of UDI (Figure 8C, filled circles) was increased as compared to that at pH 6.0 (Figure 8Ci, open circles), Table 6. Also, low pH decelerated both τ₁ (Figure 8Ci, filled histograms) and τ₂ (Figure 8Ci, filled histograms) of the UDI, Table 6. Note that different depolarization durations for UDI pulse protocols were used (see pulse protocols in Figure 8 and description in the figure legend) to account for differences in AP durations between neurons and skeletal muscles (Na_V1.2 and 1.4) vs. myocytes (Na_V1.5).

Our results suggest acidification produces differential effects on inactivation properties of Na_V1.2 and Na_V1.5, but not in Na_V1.4, suggesting that changes in pH would affect AP generation and propagation in neuronal and cardiac tissue but not in skeletal muscle.

Our experimental data were used as the basis for computer modeling (see Materials and Methods) to measure characteristics of neuronal APs at either normal or acidic pH. Figure 9 shows the results of neuronal modeling. Simulations to elicit APs were done at a continuous stimulus of −1 pA/pF in both pH 6.0 (dashed line) and pH 7.4 (solid line) over a period of 105 ms (Figure 9A). The membrane potentials of the model neurons at each pH value were plotted as a function of time (Figure 9A). Three main differences were observed between the two pH values: (1) the pH 6.0 neuron reached its maximal depolarization at 68.90 ms, faster than the pH 7.4 neuron at 76.98 ms; (2) the membrane potential at peak depolarization was 18.7 mV in the pH 6.0, a more positive depolarization than the 30.40-mV observed in the pH 7.4 neuron; and (3) the maximum hyperpolarization voltage was less negative in the pH 6.0 neuron, with a value of −67 mV compared to −74.4 mV found in the pH 7.4 neuron.

Figure 9B compares repetitive AP firing in a model neuron at pH 7.4 (solid line) and at pH 6.0 (dashed line). Data shown are for neurons injected with a constant stimulus of −20 pA/pF although simulations were also performed at stimulus amplitudes of −3, −5, −10, and −15 pA/pF with the same data trends obtained (data not shown). In the first AP, the maximum depolarization and hyperpolarization trends seen in the single AP studies, are reproduced (Table 7). The pH 7.4 neuron continues to fire APs at a rate of 94.3 Hz, but with a decreased maximum depolarization and less negative undershoot (Table 7). In contrast, the pH 6.0 model neuron failed to repetitively fire.

Since our model takes into account both fast and slow gating, we have modeled “AP chimeras” to study the specific effects of both inactivation types on the neuronal AP. Chimera 1 (Figure 9C) consists of pH 6.0 data programmed in for the activation and FI and pH 7.4 data programmed in for the slow inactivation gate. Chimera 2 (Figure 9D) has pH 6.0 data programmed in for the activation and slow inactivation gates and pH 7.4 data programmed in for the FI gate. Chimera 2 (Figure 9D) was found to have similar characteristics to the pH 7.4 neuronal model, in which the repetitive firing was preserved (Figure 9B, solid line). In contrast, Chimera 1 (Figure 9C) results were similar to the pH 6.0 model (Table 7). These modeling results suggest FI defects induced by decreased pH are responsible for the failure of the neuronal model to display repetitive AP firing.

Figures 10A,B, show the modeled sodium current during the 15th and 200th APs (firing frequency of 2.5 and 3.33 Hz, respectively) at pH 7.4 (solid line) and at pH (6.0). Plotted are the sodium current densities in pA/pF over the initial 5 ms of the cardiac AP. The sodium current is reduced and delayed in the pH 6.0 model during both 15th and 200th APs. At pH 6.0 there is a decreased level of activation and a decreased level of FI as described in Table 7; Figure 10C is the full 15th AP at both pH values; Figures 10Ci,ii show expanded views of the rising phase and repolarization phase respectively. The membrane potential of the model cardiac myocytes is plotted on the vertical axis, with −85.9 mV as the resting membrane potential, vs. a single cycle length. The maximum rise rate in the pH 6.0 model is reduced from 62.1 mV/ms, at pH 7.4, to 18.6 mV/ms, and was also delayed by 0.6 ms at pH 6.0. There also was a delay in the peak plateau potential at pH 6.0, but there was no significant difference in the AP duration (APD) between the models (Table 7). Figures 10D,Di,ii show the 200th AP as well as expanded views of the rise phase and repolarization phase. As in Figure 10C, the membrane potential of the model cardiac AP is plotted as a function of the time of a single cycle length, with the resting membrane potential at −85.9 mV. There was a decreased maximal rise rate in the pH 6.0 AP (41.1 mV/ms at pH 7.4 compared to 11.0 mV/ms at pH 6.0) and a delay in the peak plateau depolarization (Table 7). There also was a 3.7-mV difference in the peak plateau membrane potential at pH 6.0 as well as a 1.4-ms delay in the repolarization of the pH 6.0 AP.