Evaluation of the direct effect of remote ischemic preconditioning on the rabbit’s kidney by R₂’ mapping technique: an experimental study

Abstract

Background and purpose

A noninvasive and accurate indicator for evaluating direct renal effects after remote ischemia preconditioning (RIPC) is currently lacking. To explore the feasibility of R₂’ mapping in evaluating the direct effect of RIPC on rabbit kidneys and to investigate the mechanisms underlying renal changes induced by RIPC.

Methods

Eighteen healthy New Zealand rabbits were used (RIPC group, N = 12; control group, N = 6). RIPC was achieved with three cycles of bilateral hindlimb ischemia (10 min/cycle, 60 min total). Magnetic resonance imaging was performed at 1 and 24 hours after RIPC. The R₂’ values of the renal cortex, outer medulla, and inner medulla were then recorded. Femoral arterial blood was collected for blood gas analysis and measurements of electrolytes. Enzyme-linked immunosorbent assay was used to detect the levels of myeloperoxidase (MPO), malondialdehyde (MDA), and superoxide dismutase (SOD). Immunohistochemical staining was used to detect the average optical density (AOD) of hypoxia-inducible factor 1 alpha (HIF1α). One-way analysis of variance or the Kruskal–Wallis test was used to assess differences among the groups. Correlations were evaluated using the Spearman rank correlation coefficient.

Results

The R₂’ values of the renal cortex, outer medulla, and inner medulla in the RIPC groups were significantly lower than those in the control group (RIPC 1 h group: each P < .001; RIPC 24 h group: P = .002, P = .002, P < .001, respectively). MPO levels in the RIPC 1 h and 24 h groups were significantly lower than those in the control group (P = .02, P = .004, respectively). SOD levels in the RIPC 1 h group were significantly higher than in the control group (P = .001). HIF1α AOD in the RIPC 1 h and 24 h groups were significantly higher than those in the control group (both P < .001). The R₂’ values of the renal cortex, outer medulla, and inner medulla positively correlated with myeloperoxidase level (r_s=0.78, P < .001; r_s=0.78, P < .001; r_s=0.78, P < .001), and negatively correlated with superoxide dismutase level (r_s=-0.81, P < .001; r_s=-0.74, P < .001; r_s=-0.69, P = .002), and HIF1α AOD (r_s=-0.74, P < .001; r_s=-0.55, P = .02; r_s=-0.71, P < .001).

Conclusion

R₂’ mapping can quantitatively assess kidney effects after remote ischemia preconditioning, and remote ischemia preconditioning can effectively enhance renal antioxidant capacity and oxygen uptake.

Introduction

Renal ischemia-reperfusion injury (IRI) leads to acute kidney injury with high morbidity and mortality. During renal IRI progression, the cortical blood supply usually recovers fully after reperfusion, whereas the medullary blood supply remains compromised. Regional variations in blood flow distribution through the kidneys (80–85% in the cortex; 10–15% in the medulla), the countercurrent multiplier effect in the outer medullary tubules, and high Na⁺/K⁺-ATPase activity collectively contribute to medullary hypoxia. Alterations in renal medullary blood flow and blood oxygen levels are common characteristics of acute kidney injury and important early pathophysiological factors [1–3]. During renal IRI, prolonged ischemia and subsequent reperfusion can induce oxidative stress, leading to cell damage and death [4].

Currently, effective treatments for renal IRI are limited. Dexmedetomidine, desflurane, and ischemic preconditioning have shown benefits in preventing renal IRI [5–7]. However, given the individual variation in drug responses and the complexity of dose control, these interventions are challenging to implement in clinical practice. As a noninvasive, safe, and economical intervention method, remote ischemic preconditioning (RIPC) is achieved by applying brief pressure and re-releasing the limb-bound tourniquet (or cuff) several times, effectively alleviating the oxidative stress induced by ischemia [8], enhancing tissue oxygen uptake [9], and decreasing deoxyhemoglobin levels in post-IRI tissues [10]. The protective effects of RIPC have been confirmed in the heart, brain, liver, kidneys, and other organs [7, 11–13]. However, noninvasive and accurate indicators for evaluating RIPC efficacy are currently lacking.

MRI is increasingly utilized in RIPC evaluation. Blood oxygenation level-dependent MRI uses deoxyhemoglobin as an endogenous contrast agent in vivo, allowing noninvasive assessment of tissue blood oxygenation, where R₂^* is influenced by both the spin-spin and local susceptibility effects [14]. Theoretically, R₂^* is calculated as R₂^* = R₂ + R₂’. The R₂’ value eliminates the spin-spin effect, entailing advantages over conventional blood oxygenation level-dependent MRI in detecting local susceptibility changes caused by deoxyhemoglobin [15]. The T₂’ (1/R₂’) value can be used to predict the area of ischemic penumbra in patients with infarction [16, 17]. Zhang et al. [18] further demonstrated that R₂’ mapping could quantitatively detect changes in renal medullary hypoxia status. Consequently, R₂’ mapping, which utilizes deoxyhemoglobin as an endogenous contrast agent, exhibits greater sensitivity and accuracy in assessing the medullary oxygenation state.

This study investigated the feasibility of R₂’ mapping in assessing the effects of RIPC and the mechanisms underlying renal changes induced by RIPC.

Materials and methods

Animal model and grouping

Based on the pre-experimental results, the minimum sample size was estimated using PASS 2021 software. With α set at 0.05 and power at 0.8, the minimum sample size required was determined to be n = 4. To account for potential sample loss, 6 rabbits were included in each group, resulting in a final total sample size of 18 rabbits. Eighteen New Zealand rabbits (2–3 months old, 2.0–2.5 kg), purchased from Laifu Farm in Pukou District, Nanjing City (Experimental Animal Production License Number: SCXK(Su)2024-0007), were randomly allocated into the RIPC 1 h, RIPC 24 h, and control groups (n = 6 per group). Anesthesia was induced by intramuscular injection of 3% pentobarbital sodium solution (1 ml/kg), and isoflurane was inhaled through the mask (concentration 2–3%, mixed with 100% oxygen, flow rate 3 L/min) to maintain anesthesia. The RIPC model was constructed as follows. The sphygmomanometer cuff was secured at the groin level of both lower limbs. A Doppler ultrasound probe was positioned beneath the cuff to detect the blood flow sounds in the femoral artery. When the sphygmomanometer was pressurized to 200 mmHg, the blood flow sound progressively weakened and ultimately disappeared, confirming successful blood flow occlusion, lasting for 10 min. Upon deflating the cuff to 0 mmHg, the sound of blood flow reappeared and gradually intensified, indicating successful recirculation, lasting for 10 min. This process was repeated thrice. The RIPC 1 h and RIPC 24 h groups were examined using MRI at 1 and 24 h after modeling, respectively. The control group comprised healthy rabbits that did not undergo any operation but underwent an MRI. The study flowchart is shown in Fig. 1.

Fig. 1.

The study flowchart. RIPC = remote ischemic preconditioning

MRI

MRI was performed using a 3T scanner (750 W, General Electric Medical Systems, Milwaukee, WI, USA) and a 12-channel phase array flexible coil. Under anesthesia, the rabbits were placed in the left lateral position on the scanning table. The MRI sequences and parameters are listed in Table 1. MRI sequences included axial T₂-weighted imaging (T₂WI), T₂ mapping, and T₂^* mapping. The centerline of the scanning area was perpendicular to the long axis of the left kidney and was in the same section as that of the left renal hilus.

Table 1.

MRI sequences and parameters

Parameters	T2WI	T2* map	T2 map
Orientation	axial	axial	axial
TR (ms)	1792	700	933
TE (ms)	85	3.8ཞ27.2	6.9ཞ55.6
Number of echoes	1	8	8
FOV(mm2)	140 × 140	140 × 140	140 × 140
Matrix	256 × 224	128 × 128	128 × 128
Slice thickness (mm)	4.0	4.0	4.0
Flip Angle (°)	111	45	45
Scanning time (min)	1.52	1.44	4.11

T₂WI = T₂ weighted image; TR = time of repetition; TE = time of echo; FOV = field of view

Imaging analysis

All data were analyzed using vendor-provided T₂ and T₂^* fitting software on an AW 4.7 workstation (General Electric Medical Systems, Milwaukee, WI, USA). The corresponding R₂ and R₂^* maps were obtained from T₂ and T₂^* maps, respectively, using a monoexponential model. The R₂’ map was then derived using R₂^*–R₂ on the AW 4.7 workstation (Fig. 2). The largest axial slice through the renal hilum and the upper and lower slices of the renal hilum were selected for the region of interest (ROI) delineation, and the average of the three ROIs was calculated for statistical analysis. The ROIs were manually delineated in the cortex, outer medulla, and inner medulla. Each ROI was at least five pixels to avoid artifacts. Renal R₂’ values were measured in the cortex, outer medulla, and inner medulla. To test the interobserver reproducibility of the renal R₂’ values, radiologists with 10 (Observer 1) and 3 years of experience (Observer 2) drew regions of interest independently. The data from Observer 1 were selected for statistical analysis.

Fig. 2.

Representative images of R₂^* (a), R₂ (b), and R₂’ (c) maps obtained in a normal rabbit. The R₂’ map, the diagram of the region of interest, was calculated by subtracting R₂ from R₂^* in the AW 4.7 Workstation (GE Healthcare). CO = cortex; OM = outer medulla; IM = inner medulla

Hematological measurements

After MRI, 3–4 mL of femoral arterial blood was drawn from each rabbit into a tube containing ethylenediaminetetraacetic acid tripotassium (1.5 mg/mL) as an anticoagulant. According to the operation process of the Siemens blood gas analyzer (EPOC vet., Siemens Healthineers, Germany), blood gas indexes such as pH, PaO₂, PaCO₂, SaO₂, and electrolyte concentrations such as Na⁺, K⁺, Ca²⁺, Cl^– were analyzed.

Renal tissue oxidative stress indicators measurements and immunohistochemical staining analysis

The experimental rabbits were euthanized by injecting 3% pentobarbital sodium solution (3 mL/kg) through the auricular vein, and then the left kidney was removed. The tissue samples from the left kidney were homogenized in a 0.9% saline solution and centrifuged at 3000 rpm for 10 min at 4 °C. The supernatant was collected, and malondialdehyde (MDA) concentration, myeloperoxidase (MPO) and superoxide dismutase (SOD) activities were measured using an MDA test kit (G4300, Wuhan Servicebio Technology CO., LTD), an MPO test kit (A044-1, Nanjing Jiancheng Bioengineering Institute, China), and a total SOD test kit (A001-1, Nanjing Jiancheng Bioengineering Institute), respectively.

Renal tissue immunohistochemical staining measurements

Axial sections of the renal hilus, corresponding to MRI slices, were sampled vertically to the long axis of the left kidney. Tissue sections were deparaffinized in xylene and rehydrated in different alcohol concentration gradients. After rinsing in phosphate-buffered saline buffer, sections were autoclaved in 0.01 M sodium citrate buffer (pH 6.0) for antigen retrieval. The sections were then incubated with anti-hypoxia-inducible factor 1 alpha (HIF1α) antibody (bs-0737R, Bioss, China) at 4℃ overnight in a humid chamber. Antibody binding was colored with a DAB Substrate kit, and tissue sections were counterstained with hematoxylin. Positive expression was indicated by the brownish-yellow granules under a microscope. Under 400x magnification, five random fields of view were selected. The positive expression level of HIF1α was quantified using ImageJ software by measuring the average optical density (AOD). The data used for subsequent statistical analysis represent the mean AOD values derived from the five fields of view.

Statistical analysis

Statistical analyses were performed using SPSS software (version 22.0; IBM Corp., Armonk, NY, USA). The intraclass correlation coefficient was used to assess interobserver reproducibility of the R₂’ values, with values < 0.4 indicative of poor agreement; between 0.4 and 0.59, moderate agreement; between 0.6 and 0.74, good agreement; and ≥ 0.75, excellent agreement. The normality of distributions of continuous variables from the different groups was confirmed using the Shapiro-Wilk test. For normally distributed data, the values were presented as mean ± standard deviation. For non-normally distributed data, values were presented as medians with upper and lower quartiles. The homogeneity of variance was confirmed using Levene’s test. For normally distributed data with homogeneous variance, a one-way analysis of variance was used to assess differences among the three groups. For non-normally distributed or uneven variance data, statistical differences among groups were determined via Kruskal–Wallis tests. Spearman’s correlation analysis was used to evaluate the relationship of the R₂’ values with the oxidative and antioxidant markers, and HIF1α AOD. Spearman’s correlation was interpreted as negligible (0.00–0.10), weak (0.10–0.39), moderate (0.40–0.69), strong (0.70–0.89), or very strong (0.90–1.00) [19]. P < .05 was considered statistically significant.

Results

Comparison of the R₂’ values among the three groups

Representative images of T₂WI and R₂’ maps in the control, RIPC 1 h, and RIPC 24 h groups are shown in Fig. 3. The R₂’ values of the renal cortex, outer medulla, and inner medulla in the three groups are presented in Table 2. The interobserver agreements for the R₂’ values of the cortex, outer medulla, and inner medulla were all excellent, with the intraclass correlation coefficient values of 0.925 (95% CI: 0.799, 0.972), 0.970 (95% CI: 0.920, 0.989), and 0.960 (95% CI: 0.895, 0.985), respectively. In the control group, outer medulla signals were significantly higher than those of the inner medulla and cortex. In the RIPC 1 h and 24 h groups, the outer medulla signal was significantly lower than that in the control. In the RIPC 1 h and 24 h groups, the R₂’ values of the renal outer medulla were significantly lower than those in the control group (P < .001, P = .002, respectively), the R₂’ values of the cortex and inner medulla were also slightly lower than those in the control group (cortex: P < .001, P = .002; inner medulla: P < .001, P < .001; respectively). In the RIPC 24 h group, the R₂’ values of the outer medulla were higher than those in the RIPC 1 h group (P < .001). However, the R₂’ values of the cortex and inner medulla were not different between the RIPC 1 h and 24 h groups (P = .18, P = .07, respectively).

Fig. 3.

Representative T₂WI, R₂’ maps, and HIF1α immunostaining images for the control, RIPC 1 h, and RIPC 24 h groups. On the T₂WI, the renal cortex, outer medulla, and inner medulla are clearly defined in the three groups. On the R₂’ maps, the signal of the outer medulla in the control group was significantly higher than that of the inner medulla and cortex. In the RIPC 1 h and RIPC 24 h groups, the signal of the outer medulla was significantly lower than that in the control group, with the lowest signal observed in the RIPC 1 h group. On the HIF1α immunostaining images, HIF1α is detected in the nucleus of proximal tubule cells after RIPC. Magnification: ×400. RIPC = remote ischemic preconditioning; HIF1α = hypoxia-inducible factor 1 alpha

Table 2.

The R₂’ values for the control, RIPC 1 h, and RIPC 24 h groups

	Control group (n = 6)	RIPC 1 h group (n = 6)	RIPC 24 h group (n = 6)	F value	P value
R2’ values of the cortex (1/sec)	11.40 ± 1.59	7.98 ± 0.64	8.93 ± 1.09	13.53	< 0.001
R2’ values of the outer medulla (1/sec)	20.29 ± 1.58	11.48 ± 0.73	17.98 ± 0.68	107.41	< 0.001
R2’ values of the inner medulla (1/sec)	10.96 ± 1.39	7.48 ± 0.20	8.43 ± 0.36	27.57	< 0.001

Values are presented as the mean ± standard deviation (SD). RIPC = remote ischemic preconditioning

Comparison of hematological parameters

Hematological results are summarized in Table 3, with significant differences in PaO₂, PaCO₂, SaO₂, and K⁺ levels among the three groups (P = .004, P = .003, P = .03, and P = .007, respectively). PaO₂, PaCO₂, and SaO₂ levels in the RIPC 1 h group were higher than those in the control group (P = .003, P = .006, and P = .047, respectively), as were also noted for the RIPC 24 h group values (P = .003, P = .009, and P = .01, respectively). The K⁺ concentration in the RIPC 1 h group was lower than that in the control group (P = .01). The PaCO₂ level in the RIPC 24 h group was lower than that in the RIPC 1 h group (P = .001).

Table 3.

Hematological results for the control, RIPC 1 h, and RIPC 24 h groups

Indicators	Control group (n = 6)	RIPC 1 h group (n = 6)	RIPC 24 h group (n = 6)	F/H values	P values
pH	7.32 ± 0.05	7.33 ± 0.05	7.39 ± 0.50	3.52	0.06
PaO2 (mmHg)	317.83 ± 62.62	428.30 ± 44.31	426.20 ± 53.12	8.25	0.004
PaCO2(mmHg)	45.57 ± 3.50	50.38 ± 1.86	43.48 ± 2.98	9.17	0.003
SaO2 (%)	99.90 (99.88–99.93)	100.00 (99.98–100.00)	100.00 (100.00–100.00)	10.00	0.007
Na+ (mmol/L)	140.50 ± 1.38	140.00 ± 1.55	140.67 ± 2.07	0.25	0.78
K+ (mmol/L)	4.30 ± 0.50	3.55 ± 0.34	3.83 ± 0.45	4.50	0.03
Cl− (mmol/L)	108.33 ± 2.42	106.00 ± 4.52	108.00 ± 3.85	0.70	0.51
Ca2+ (mmol/L)	1.55 ± 0.17	1.51 ± 0.18	1.49 ± 0.15	0.20	0.51

Data are mean ± standard deviation (SD) for normally distributed variables, median and interquartile range (in parentheses) for skewed variables. RIPC = remote ischemic preconditioning

Comparison of renal oxidative and antioxidant markers among the three groups

Renal oxidative and antioxidant markers are summarized in Table 4. There were significant differences in MDA, MPO, and SOD levels among the three groups (P = .003, P = .02, and P = .003, respectively). In the RIPC 1 h and 24 h groups, MPO levels were significantly lower than those in the control group (P = .02, P = .004, respectively). SOD levels in the RIPC 1 h group were significantly higher than in the control (P = .001) and RIPC 24 h groups (P = .01). MDA levels in the RIPC 24 h group were significantly higher than in the control group (P = .001).

Table 4.

Renal tissue oxidation and antioxidant markers for the control, RIPC 1 h, and RIPC 24 h groups

Markers	Control group (n = 6)	RIPC 1 h group (n = 6)	RIPC 24 h group (n = 6)	F/H values	P values
MDA (nmol/mg prot)	0.63 (0.55–0.84)	0.50 (0.36–0.74)	1.13 (0.74–1.43)	8.29	0.003
MPO (U/g prot)	0.26 (0.22–0.33)	0.14 (0.10, 0.15)	0.14 (0.14–0.17)	11.92	0.02
SOD (U/mg prot)	1078.38 ± 181.35	1470.19 ± 171.29	1183.92 ± 151.63	10.00	0.003

Data are mean ± standard deviation (SD) for normally distributed variables, median and interquartile range (in parentheses) for skewed variables. RIPC = remote ischemic preconditioning; MDA = malondialdehyde; MPO = myeloperoxidase; SOD = superoxide dismutase

Comparison of the HIF1α AOD

HIF1α immunohistochemistry of renal tissue revealed a brownish-yellow positive staining pattern. In the control group, HIF1α was predominantly localized in the cytoplasm of proximal tubules, whereas in the RIPC group, it was primarily detected in proximal tubule nuclei. The AOD values of renal HIF1α in the RIPC 1 h and 24 h groups were significantly higher than those in the control group, with values of (0.168 ± 0.003) vs. (0.147 ± 0.002) and (0.170 ± 0.003) vs. (0.147 ± 0.002), respectively (both P < .001). No statistically significant difference was observed in renal HIF1α AOD between the RIPC 1 h and 24 h groups (P > .05).

Correlation between the R₂’ values with oxidation, antioxidant markers, and HIF1α AOD

Linear correlation diagrams between the R₂’ values and MDA, MPO, SOD, and HIF 1α AOD are shown in Figs. 4, 5 and 6. Strong positive correlations were found between cortex, outer medulla, and inner medulla R₂’ values and MPO activity (r_s =0.78, P < .001; r_s =0.78, P < .001; r_s =0.78, P < .001, respectively). Strong negative correlations were found among cortex, and outer medulla R₂’ values and SOD level (r_s =-0.81, P < .001; r_s =-0.74, P < .001, respectively). A moderate negative correlation was found for inner medulla R₂’ values and SOD level (r_s =-0.69, P = .002). Strong negative correlations were found among cortex, and inner medulla R₂’ values and HIF1α AOD (r_s =-0.74, P < .001, r_s =-0.71, P < .001, respectively). A moderate negative correlation was found in the outer medulla R₂’ values with HIF1α AOD (r_s =-0.55, P = .02).

Fig. 4.

Linear correlation diagram between the R₂’ values of the CO, OM, and IM with the levels of MDA (a-c), and MPO (d-f). Spearman’s rank correlation coefficient showed a positive correlation between the R₂’ values and MPO level. No significant correlation was found between the R₂’ values and MDA level. MDA = malondialdehyde; MPO = myeloperoxidase; CO = cortex; OM = outer medulla; IM = inner medulla

Fig. 5.

Linear correlation diagram between the R₂’ values of the CO, OM, and IM with the SOD level (a-c). Spearman’s rank correlation coefficient showed a negative correlation between the R₂’ values of SOD level. SOD = superoxide dismutase; CO = cortex; OM = outer medulla; IM = inner medulla

Fig. 6.

Linear correlation diagram between the R₂’ values of the CO, OM, and IM with the HIF1α AOD (a-c). Spearman’s rank correlation coefficient showed a positive correlation between the R₂’ values and the HIF1α AOD. HIF1α = hypoxia-inducible factor 1 alpha; CO = cortex; OM = outer medulla; IM = inner medulla

No significant correlation was found between renal cortex, outer medulla, and inner medulla R₂’ values and MDA content (r_s=0.04, P = .88; r_s =0.24, P = .34; r_s =0.24, P = .33, respectively).

Discussion

This study used R₂’ mapping to assess renal remote ischemia preconditioning models, leveraging its advantages for detecting changes in renal blood oxygenation. In the remote ischemia preconditioning groups, the renal outer medullary R₂’ values and myeloperoxidase level were lower, while PaO₂, superoxide dismutase level, and hypoxia-inducible factor 1 alpha average optical density were higher than in the control group. The renal R₂’ values were negatively correlated with superoxide dismutase level and hypoxia-inducible factor 1 alpha average optical density, while positively correlated with myeloperoxidase level, indicating that remote ischemia preconditioning may enhance renal hypoxic conditions and thus upregulate the renal antioxidant capacity.

In the RIPC groups, the R₂’ values of the renal outer medulla were lower than those in the control group, indicating that RIPC could effectively improve the physiological hypoxia of the renal outer medulla. Firstly, an increase in PaO₂ may contribute to enhancing blood oxygen levels within the kidneys. Furthermore, HIF1α plays a key role in adapting to conditions such as ischemia. Ischemia triggers the formation of a HIF1α heterodimer that translocates into the nucleus, where it acts as a transcriptional activator of target genes [20]. A clinical study demonstrated that RIPC stimulus significantly increases the HIF1α levels [21], which can upregulate erythropoietin and vascular endothelial growth factor to improve renal microcirculation, potentially facilitating efficient oxygen delivery [22, 23]. Additionally, prior studies have demonstrated that RIPC effectively regulates vascular smooth muscle tone and enhances organ perfusion through the activation of inducible nitric oxide synthase, which specifically increases nitric oxide production in glomeruli and proximal tubules [24, 25]. Concurrently, HIF1α drives metabolic shifts toward anaerobic pathways by upregulating glycolysis-related enzymes, thereby reducing deoxyhemoglobin content, ultimately resulting in decreased R₂’ values [26, 27]. Siedek et al. [28] implemented a RIPC intervention in the right upper limb of healthy volunteers and similarly ascertained that the R₂^* values of the renal medulla decreased after RIPC, which is consistent with the present findings.

In this study, a decrease in MPO and an increase in SOD were observed in renal tissues following RIPC. SOD is a critical antioxidant enzyme, serving to eliminate superoxide radicals and thus averting cellular injury [29]. Furthermore, MPO, a hallmark of neutrophil activation, serves as an indicator for neutrophil infiltration [30]. Previous studies [31, 32] have demonstrated that RIPC can enhance the activity of SOD through neuroreflex pathways and humoral responses. This effect is believed to result in the inhibition of lipid peroxidation and subsequent alleviation of oxidative stress. A large number of animal studies confirmed that SOD activity in renal tissue increased significantly after RIPC, and the overall antioxidant capacity of the body improved, thus effectively reducing subsequent IR damage [33, 34].

Compared to the RIPC 24 h group, the renal R₂’ value, MDA content, and MPO activity were lower, while SOD activity was higher in the RIPC 1 h group. These findings suggest that early RIPC may enhance renal protection. However, there is no consensus regarding the renal protective effects of RIPC at different time points. Hou et al. [35] demonstrated that late-stage RIPC offered superior renal protection than early-stage RIPC in patients undergoing laparoscopic surgery. In contrast, Veighey et al. [36] reported that early-stage RIPC had a more pronounced effect on improving renal function. In future research, the RIPC + IRI model will be employed to investigate the benefits and drawbacks of the protective effect of RIPC during the early and late phases.

This study has some limitations. Firstly, the renal effect of RIPC was verified only in healthy rabbits, and its protective effects on renal function or structure have not been clearly demonstrated in pathological environments. However, this is already included in our next research plan, and we will further explore the protective effects of RIPC in kidneys with IRI. Second, the procedural implementation of RIPC is currently not standardized; the RIPC model adopted in this study is based on the method of Verga and colleagues [7]. Thirdly, this study did not make a lateral comparison of R₂’ mapping technology and BOLD MRI. This was because the research team had previously confirmed the feasibility of evaluating the level of oxygenation using R₂’ mapping [18].

In conclusion, quantitative R₂’ mapping can be used to evaluate the effects of remote ischemia preconditioning on rabbit kidneys in a noninvasive manner. The R₂’ values among the different time groups and the control group differed, indicating an improved renal hypoxia status due to remote ischemia preconditioning. Furthermore, the renal effects of remote ischemia preconditioning are associated with enhanced renal antioxidant capacity and kidney oxygen uptake.

Abbreviations

RIPC

Remote ischemia preconditioning

MPO

Myeloperoxidase

MDA

Malondialdehyde

SOD

Superoxide dismutase

AOD

Average optical density

HIF1α

Hypoxia-inducible factor 1 alpha

IRI

Ischemia-reperfusion injury

T₂WI

T₂-weighted imaging

CO

Cortex

OM

Outer medulla

IM

Inner medulla

ROI

Region of interest

Author contributions

ZY. B, ZY. X, LF. H contributed to the experimental studies, data analysis, and writing the initial manuscript. XT. Y contributed to the experimental studies and investigation. JL. D, J.C contributed to the supervision and validation. L. P and W. X contributed to conceptualization, methodology, and manuscript revision. W. X, L. P and ZY. X contributed to funding acquisition. All authors reviewed and approved the final manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (No. 82001763, 82171901, 82302141, and 82471966), the Natural Science Foundation of Jiangsu Province (No. BK20241776), and the Changzhou Science and Technology Program (No. CJ20244015).

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The experimental rabbits used in this study were from Laifu Farm in Pukou District, Nanjing City (Experimental Animal Production License Number: SCXK(Su)2024-0007) and received informed consent from the farm director. This study was approved by the Ethics Committee for Animal Experimentation in the Jiangsu Aniphe Biolaboratory Inc.(JSAB24019M) and adhered to the Guide for the Care and Use of Laboratory Animals.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.