Twenty-four 4-week-old male spontaneously hypertensive rats were purchased from Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China). All rats were raised in 12-h light/12-h dark cycle environment and had free access to water and food. This study was approved by Ethics Committee for Animal Experimentation of China Pharmaceutical University. All efforts were made to minimize animal suffering.

Ramipril was supplied by Kunshan Rotam Reddy Pharmaceutical Co., Ltd. (Kunshan, China). Systolic blood pressure was measured with ALC-NIBP (tail-cuff method) from ALCBIO (Shanghai, China). Iodine [¹²⁵I] Angiotensin II Radioimmunoassay Kit was obtained from Beijing North Institute of Biological Technology (Beijing, China).

All rats were acclimatized for 1 week. From the age of 5 week, 24 SHR were randomly assigned to three groups: one disease group and two ramipril treatment groups: standard treatment group (receiving ramipril 2 mg/kg/day) and intensive treatment group (receiving ramipril 10 mg/kg/day). Rats in two treatment groups were given ramipril by gavage at 9:00 AM every day from 18 to 21-week-age. SBP were measured weekly. Six hundred microliter of blood sample was collected via tail vein once a week with collection time fixed at 2:00 PM, blood samples were anticoagulated with EDTA and centrifuged at 4000 g for 15 min immediately. Plasma samples were aliquoted and stored at −80°C until analysis. At the age of 21 week, all rats were sacrificed by cervical dislocation.

The protocol for blood pressure measurement was designed based on the method introduced in the works of Whitesall et al. (2004) and Kubota et al. (2006). During the first week, all rats were acclimated to restraint, tail-cuff inflation, and heating. Rats were placed in plastic restrainers with heating pad remaining at 33~34°C. The instrument (ALC-NIBP, ALCBIO; Shanghai, China) automatically takes ten 30-s measurements. The values of systolic blood pressure were recorded when more than five consecutive stable readings were available. The highest and lowest readings were discarded, and the remaining readings were averaged for one data point.

Plasma asymmetric dimethylarginine (ADMA) was measured using an HPLC-MS/MS method introduced by He (He et al., 2013). Plasma nitric oxide (NO) is determined by measuring the stable end products, nitrite and nitrate, which is described in the work of Moshage (Moshage et al., 1995). Plasma angiotensin II (Ang II) was measured using radioimmunoassay with commercial kit obtained from Beijing North Institute of Biological Technology (Beijing, China).

The general structure of the disease progression model is shown in Figure 2. Basically, the model was composed with three components: one defined the natural disease progression in SHR without treatment as disease model; two of which described ameliorated hypertensive disease progression with two different doses of ramipril intervention as treatment model. Four turnovers were applied for describing the dynamics of plasma Ang II, plasma ADMA, plasma NO, and SBP, which are represented by the following four equations:

In which, C_ANG, C_ADMA, C_NO, and SBP indicate plasma Ang II, ADMA, NO concentration, and SBP level, respectively. In this model, plasma Ang II was the marker that triggers the cascade of downstream reactions. Plasma Ang II is assumed to be formed at a zero-order constant rate (k_{in_ANG}) and degraded by the first-order constant rate (k_{out_ANG}). The degradation of Ang II is stimulated through a negative regulatory feedback loop (ES_ANG; Zhou et al., 2012), which is characterized with a linear model represented with ES_ANG. In two treatment groups, plasma Ang II level is subjected to an inhibitory effect from ramipril (EI_RAMI), EI_RAMI is a drug-specific parameter. The dose of ramipril was indicated by parameter DOSE. DOSE was fixed at 0 when model was fitted in disease group, while at 2 or 10 in two treatment groups, respectively. ADMA is synthesized by Protein Arginine Methyltransferase (PRMT) and eliminated mainly through dimethylarginine dimethylaminohydrolase (DDAH) hydrolysis. Prior to occurrence of disease, plasma ADMA level remains at a relatively stable situation, which is represented by a zero-order constant rate (k_{in_ADMA}) for production and a first-order constant rate (k_{out_ADMA}) for elimination. According to the previously mentioned mechanism, elimination of ADMA is restrained with Ang II (IA_ANG[m]).IA_ANG[m] represents the inhibitory effect that Ang II exerts on DDAH, where m indicates the number of transit compartments that is applied to simulate the inhibition of ADMA elimination by Ang II. A zero-order constant rate k_{in_NO} and a first-order constant rate k_{out_NO} are used to describe the generation and degradation of plasma NO, respectively. In this system, activity of NOS is stimulated by elevated blood pressure according to previous research (Vaziri et al., 1998), which is simulated with a linear effect represented by parameter ES_SBP. The suppression of NOS activity by plasma ADMA and plasma Ang II are described with two transduction procedures IN_ADMA[n] and IN_ANG[o], respectively. n and o indicate the number of the transit compartments that is required for describing the effects. In this model, systolic blood pressure is assumed to be input and output in zero-order rate (k_{in_SBP}) and first-order rate (k_{out_SBP}), respectively, where Ang II contributes to the climb of systolic blood pressure by causing vasoconstriction, while NO eases systolic blood pressure through vasodilation effect, which are represented with two separate series of transit compartments ES_ANG[p] and ES_NO[q].

At the beginning of the disease progression, plasma Ang II level is described with the equation below:

In this model, Ang II accumulation is assumed to be spontaneous and no other markers in this system would affect the procedure of accumulation.

Plasma ADMA was assumed to be maintained at a steady level before the initiation of the disease development, which is reflected with the equation below:

The turnover of plasma ADMA was mainly affected by the activity of DDAH, which was inhibited by Ang II-induced ROS due to its high sensitivity to oxidative environment. This inhibitory effect was simulated by a series of transit compartments, which are represented by the following equations:

This transduction effect was assumed to be initiated by a disease factor OX_DDAH, where m indicates the number of transit compartments that were applied to describe the inhibition of Ang II-mediated ROS on the elimination of ADMA; each transit compartment was connected by a turnover rate constant kt₁. Different transit compartment numbers were evaluated to find a number that sufficiently captured the stimulation.

The initial plasma NO level is represented with the following equation:

During disease progression, the turnover of NO was mediated by other three markers in this system. ADMA inhibits the synthesis of NO directly by competitive binding to NOS. A series of transit compartments was applied to describe this effect:

This transduction effect was assumed to be initiated by a disease factor IN_NOS, where n indicates the number of transit compartments that were applied to simulate the inhibitory effect of ADMA on the generation of NO; each transit compartment was connected by a turnover rate constant kt₂. Different transit compartment numbers were evaluated to find a number that sufficiently captured the inhibitory effect from ADMA on NOS.

Ang II-induced generation of ROS would sharply cut down the activity of NOS. To mimic this effect, a series of transit compartments were utilized:

This transduction effect was assumed to be initiated by a disease factor OX_NOS, where IN_ANG (o) indicates the number of transit compartments that were applied to describe the inhibition from Ang II-induced ROS on the generation of NO; each transit compartment was connected by a turnover rate constant kt₃. Different transit compartment numbers were evaluated to find a number that sufficiently captured the stimulation.

SBP continues to climb during the growth of SHR till the age of 16–17 weeks. At the age of 5 weeks, the SBP of SHR is described by the equation below:

In the system we investigated, SBP was adjusted by Ang II and NO in a manner of counterbalance. Ang II exerted its pressor effect by causing vasoconstriction through binding to AT1 receptors. On the contrary, the pressor effect was being counterbalanced by vasodilator NO. This effect could be described through two series of transit compartments, which are represented by the following equations, respectively.

The first group of equations is proposed to represent vasopressor effect:

VCON was assumed to be the initiative factor of vasoconstriction, p indicates the number of transit compartments that were applied to describe the vasoconstriction effect from Ang II; each transit compartment was connected by a turnover rate constant kt₄. Different transit compartment numbers were evaluated to find a number that sufficiently captured the stimulation.

The vasodilation effect of NO was represented with the equations below:

The initiation of the vasodilation from NO was assumed to be initiated by VDIL, q indicates the number of transit compartments that were applied to describe the vasodilation effect of NO; each transit compartment was connected by a turnover rate constant kt₅. Different transit compartment numbers were evaluated to find a number that sufficiently captured the stimulation.

The hypertensive disease progression combined with ramipril's effect was modeled using Phoenix 6.4 (CERTARA). The data from total 24 rats in the disease group and treatment groups were pooled together for baseline analysis in the initial 13 weeks. In the following 4 weeks, 8 rats in disease group were contributed continually for baseline modeling, and 8 rats in standard treatment group were used to estimate the drug effect parameter EI_RAMI. Eight rats in intensive treatment group were used to validate the drug effect modeling. The validation was performed by visual predictive check (VPC). Estimates of parameters from the standard treatment group were used for the performance of VPC. The baseline parameters were accordingly fixed in drug effect estimation, assuming the baseline in treatment groups did not change evidently from the disease group. The dose of ramipril was represented with the parameter DOSE. DOSE was fixed at 0 in the disease group, while 2 and 10 in two treatment groups, respectively. Model evaluation was performed using non-parametric bootstrap analysis, introduced in previous research (Chen et al., 2009). Random draws of individual data from the original dataset was repeated 100 times. The stability of the final model was evaluated by comparing the model parameter estimates from the average values of new datasets with that obtained from the fit of the average values of original dataset.

Model simulations were conducted using mean estimates obtained from the model to observe the effects on plasma NO turnover throughout the disease progression from the three disease factors: OX_DDAH, IN_NOS, and OX_NOS. OX_DDAH, IN_NOS, or OX_NOS was fixed at zero in each simulation respectively, which simulates the blockade of such disease procedure.

The time course of plasma angiotensin II (Ang II), asymmetric dimethylarginine (ADMA), nitric oxide (NO) and systolic blood pressure (SBP) variations during 5 to 21-week-age are shown in Figure 3. In disease group, the change of SBP could be divided into three stages. At the first stage, SBP climbed quickly from under 140–180 mmHg during the first 4–5 weeks. SBP then grew to around 200 mmHg at the age of 17 weeks in a more slowly pace and remained at this level afterwards. Ramipril showed significant antihypertensive effect from the data of two treatment groups with a good dose-effect relationship. After 4 weeks' therapy, SBP reached 146.8 ± 13.44 mmHg in standard treatment group and 127.4 ± 11.9 mmHg in intensive treatment group, respectively. Time course of plasma Ang II level in all three groups of SHR went accordingly with the variation of SBP. Higher dose of ramipril also showed a stronger effect on plasma Ang II. Plasma ADMA, and NO did not vary sharply compared to SBP and plasma Ang II. Nevertheless, the accumulation of ADMA was observed in disease group. Plasma NO was maintained at a relatively higher level before a drop at the age of 12 weeks in all groups. Ramipril increased plasma NO during the 4-week therapy. It is worth mentioning that administration of 2 mg/kg ramipril successfully dragged SBP to 146.8 ± 13.44 mmHg, reversed the accumulation of plasma ADMA and increased plasma NO level, compared to disease group. However, a higher dose (10 mg/kg) of rampril with better antihypertensive effect (dragging SBP to 127.4 ± 11.9 mmHg) failed to exert further attenuation of plasma ADMA and NO.

The profiles of SBP, plasma Ang II, ADMA, and NO throughout disease progression were reasonably fitted with our proposed model. The predicted values of SBP, plasma Ang II, ADMA, and NO in disease group (Figure 4) and standard treatment group (Figure 5) were fitted with the mean values from the original data set. Parameter estimates and the optimized transit compartment numbers are listed in Table 1. Parameter estimates obtained from the fit of original mean data were within the mean ± SD estimates of the bootstrap replicates. The result of VPC for intensive treatment group has been demonstrated in Figure 6. The observed values are well within the range between 5 and 95 percentiles of 1000 simulated values. The conditional weighted residuals (CWRES) were randomly and homogenously distributed around 0 (Figures 7, 8). The results suggested a reasonable precision in the parameter estimates for the final model.

Based on mean parameter estimates of the model, simulations were performed to predict the fraction of three disease factors contributed to the turnover of plasma NO (Figure 9). Each of the three disease factors (OX_DDAH, OX_NOS, IN_NOS) was fixed at 0 for each simulation, assuming the blockade of such disease procedure initiated by the corresponding disease factor. The locations of simulated blockades are shown in Figure 1. NO production was affected by three disease factors with different extensions (Figure 9). The blockade of IN_NOS showed the most significant improvement in NO production (Figure 9, blue line). While blocking Ang II-mediated inhibition of dimethylarginine dimethylaminohydrolase (DDAH) activity (OX_DDAH) showed much milder effects on NO production (Figure 9, purple line). Compared with them, blocking the direct effect of Ang II-mediated oxidative stress on NOS (OX_NOS) has the minimum improvement on NO production (Figure 9, red line). Simulated data indicate that Ang II inhibited NO production mainly through affecting ADMA hydrolysis rather than suppressing NOS activity directly.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.