Naringin (Cat. No. 71162) and Streptozotocin (STZ) (Cat. No. S0130) were obtained from Sigma-Aldrich Chemical Co. (Burlington, MA, USA). Glimepiride (Amaryl) was purchased from Sanofi-Aventis (Cairo, Egypt). All other chemicals and reagents used were of analytical grade and purchased from standard commercial sources at the highest purity available.

Adult male, healthy Sprague-Dawley rats (n = 40, aged 9–12 weeks, weighing 150–200 g) were purchased from the National Research Centre (NRC) in Giza, Egypt. The animals were maintained under standard laboratory conditions in clean polypropylene cages (5 rats/cage), with a temperature of 22 ± 2°C, humidity (30–50% RH), and a 12-hour light/dark cycle. They had free access to water and standard rat chow throughout the adaptation period. Experimental procedures were conducted in the animal house of Damietta Faculty of Medicine, Al-Azhar University, Egypt.

After a two-week adaptation period, DM was induced via a single intraperitoneal injection of STZ (45 mg/kg body weight [BW]) dissolved in 0.1 M citrate buffer (pH 4.5) [15], whereas control animals received an equal volume of the vehicle alone. Fasting blood glucose (FBG) levels were assessed 72 hours post-injection using a glucometer (Easy Gluco, Infopia, Korea); subsequently, only animals exhibiting concentrations exceeding 250 mg/dL were included in the diabetic cohorts for subsequent pharmacological evaluation.

Immediately following the confirmation of diabetes, the standard rat chow was replaced with a high-fat diet (HFD). This dietary regimen was maintained for a duration of four weeks to facilitate the development of diabetic complications, specifically peripheral neuropathy. The HFD consisted of 60% of total kcal (daily energy intake) from fat, 20% of total kcal from carbohydrates, and 20% of total kcal from protein (comprising lard, cholesterol, and standard nutrients) [16].

The rats were then divided into four groups as follows: Group 1, normal control (NC): 10 non-diabetic rats received citrate buffer (pH 4.5) and normal drinking water. Group 2, diabetic control (DC): 10 diabetic rats received normal drinking water. Group 3, naringin-treated diabetic rats (NGN-D): 10 diabetic rats, treated with naringin (100 mg/kg BW/day) by intragastric gavage for 4 weeks [17]. Group 4, glimepiride-treated diabetic rats (GD-D): 10 diabetic rats received glimepiride (0.5 mg/kg BW/day) orally for 4 weeks [18].

Initial BW was measured at the beginning of the experiment, and final BW was recorded at the end of the experiment. The next day after treatment, hyperalgesia was assessed by several behavioral tests, blood samples were collected from retro-orbital veins, and the rats were then anesthetized via i.p. injection of a mixture of 50 mg/kg ketamine hydrochloride and 5 mg/kg xylazine [19] and killed by decapitation. The animals’ brains were removed, washed with ice-cold saline after removing the adhering tissue, and stored on ice. The animal experiments were approved by the Ethical Review Committee of the Faculty of Medicine, Al-Azhar University, Damietta, Egypt (DFM-IRB 00012398-11-03-002).

A comprehensive visual timeline detailing the spanning adaptation, DN confirmation, treatment, and assessment phases is illustrated in Figure 1.

For measurement of insulin, interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α), plasma was separated by collecting a portion of the blood into heparinized tubes and centrifuging it at 600 × g for 15 min. Another portion of the blood was centrifuged at 3,000 × g for 15 min to separate the serum for determination of glucose, triglyceride (TG), total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), and nitric oxide (NO).

On the other hand, the stored brain tissues were rinsed with ice-cold saline, dried, sectioned into small pieces, and then homogenized in ice-cold buffer (10 mM KH₂PO₄; 20 mM EDTA; 30 mM KCl). The resulting homogenate was centrifuged at 4°C (1,000 × g for 10 min), and the isolated supernatant was used to determine brain oxidants and antioxidant defense markers.

Serum glucose, TG, TC, LDL-C, HDL-C, proinflammatory cytokines including TNF-α, and IL-6 were measured by enzymatic methods using commercially available kits (RayBiotech), following the manufacturer’s recommendations.

Brain level of malondialdehyde (MDA) was measured following the method described by Ohkawa et al. [20]. Superoxide dismutase (SOD) activity was measured by the conventional technique of Marklund S and Marklund G [21]. NO and catalase (CAT) enzyme activity were calorimetrically assessed according to Montgomery and Dymock [22] and Aebi [23], respectively. Glutathione peroxidase (GPx) enzyme activity was assessed following the method of Paglia and Valentine [24] and Factor et al. [25] by measuring NADPH oxidation at 340 nm in the presence of glutathione.

Primary and secondary antibodies were utilized in accordance with validated manufacturer protocols. Astrocytic activation was quantified in brain tissue sections using a rabbit polyclonal anti-Glial Fibrillary Acidic Protein (GFAP) primary antibody (Cat. No. ab7260, Abcam, Cambridge, UK; dilution 1:1000). Microglial profiling was conducted using a rabbit polyclonal anti-ionized calcium-binding adapter molecule 1 (Iba1) antibody (Cat. No. 019-19741, Wako Pure Chemical Industries, Osaka, Japan; dilution 1:500). Tissue sections were subsequently incubated with a horseradish peroxidase (HRP)-conjugated goat anti-rabbit IgG secondary antibody (Cat. No. sc-2004, Santa Cruz Biotechnology, Dallas, TX, USA; dilution 1:2000). Visualizations and cellular quantification were performed via light microscopy, with negative control sections processed omitting the primary antibodies to confirm staining specificity.

Diabetes-induced hyperalgesia was evaluated in the diabetic rats by observing pain thresholds and pain perception using behavioral tests including hot plate, tail immersion, and mechanical sensitivity (von Frey) tests [26].

In the hot plate test, rats were placed individually on a hot plate (54 ± 0.1°C), and the latency to front and hind paw licking, rubbing, or jumping to avoid the heat was determined. To prevent thermal injury to the paw tissue, a maximum cut-off time of 30 s was strictly enforced, adapting safety parameters established in previous literature [27].

The tail immersion test was conducted by immersing the distal portion of the rat’s tail into a hot water bath maintained at 55 ± 0.5°C. The latency period before the tail withdrawal reflex was recorded; a shorter latency indicates thermal hyperalgesia. To ensure optimal ethical care and prevent thermal tissue damage, a maximum cut-off time of 15 seconds was strictly enforced to terminate stimulus exposure in the absence of a spontaneous reflex [28].

In the mechanical sensitivity (von Frey) test, rats were placed individually in mesh-floored boxes and allowed to adapt for 20 min. Calibrated von Frey filaments were pressed perpendicularly on the plantar surface of the hind paw with a sufficient force to bend the filament for 6 s. With animals that did not give a response, filaments of the next-greater force were applied, while in the presence of a response, filaments of the next-lower force were used. Each animal underwent 4 to 5 trials separated by 5-min intervals. The mean threshold force, expressed in grams, required to trigger a paw withdrawal reflex was calculated and used for statistical analysis [29].

Data were analyzed using SPSS software (version 22.0; IBM Corp., Armonk, NY, USA). The normality of data distribution and homogeneity of variance were assessed using the Shapiro-Wilk and Levene’s tests, respectively. Quantitative variables are expressed as mean ± standard error of the mean for n = 10 animals per group. Significant differences between multiple groups were determined using one-way analysis of variance (ANOVA), followed by Tukey’s post-hoc test for pairwise multiple comparisons. Statistical significance was defined as p < 0.05. Results were further categorized as highly significant at p < 0.001, while values of p > 0.05 were considered statistically non-significant.

As shown in Table 1, there were no significant differences (p > 0.05) in the BW between the studied groups at the beginning of the experiment. At the end of the experiment, diabetic rats showed a decrease in the final BW, with a significantly reduced weight gain (p < 0.01) compared to the NC rats. Treatment with naringin or glimepiride resulted in significant weight gain and recovery of the reduced BW compared with the DC rats (p < 0.01). Table 1 also shows that naringin and glimepiride significantly modulate the glycemic status of diabetic rats by decreasing plasma glucose and increasing insulin levels compared with DC rats (p < 0.01).

The results of hot-plate and tail-immersion tests revealed a significantly decreased pain threshold in DC rats compared to the NC rats (p < 0.01). Both tests revealed a significant increase in nociceptive threshold in both naringin-treated and GD-D rats as compared to DC rats (p < 0.01), with a more pronounced response in the tail-immersion test to naringin compared to glimepiride (p < 0.05) (Figure 2). Also, the results of the mechanical sensitivity (von Frey) test revealed a significant reduction in the tactile withdrawal threshold in DC rats compared with the NCs (p < 0.01), which was significantly corrected when diabetic rats were treated with either naringin or glimepiride (Figure 2).

As shown in Table 2, diabetic rats reported significantly higher levels of TG, TC, LDL-C, TNF-α, and IL-6, with a significant reduction in HDL-C compared with the NC rats. Interestingly, the naringin and glimepiride-treated diabetic groups experienced ameliorated alterations in NO, serum lipids, as well as plasma IL-6 and TNF-α, with almost the same degree of efficacy for all observed parameters except for the proinflammatory cytokines, where the anti-inflammatory effect of naringin was more pronounced than that of glimepiride (p < 0.05).

Table 3 shows the effect of treatment with naringin and glimepiride on brain oxidants and antioxidant defense markers in diabetic rats, where the DC rats had a significant increase in plasma NO level and brain content of MDA, with a significant decrease in brain GSH, GPx, SOD, and CAT compared to the NC rats. In contrast, the naringin-treated and GD-D showed nearly normalized brain levels of MDA, GSH, GPx, SOD, and CAT, with no significant difference between the two drugs.

While both naringin and glimepiride effectively managed hyperglycemia and improved the lipid profile, naringin demonstrated a significantly greater capacity to attenuate neuroinflammation and thermal hyperalgesia. Specifically, naringin outperformed glimepiride in reducing pro-inflammatory cytokines (TNF-α and IL-6) and increasing latency in the tail immersion test. In contrast, both treatments yielded comparable improvements in oxidative stress markers (MDA, GSH, GPx, SOD, and CAT) and lipid parameters (TG, TC, LDL-C, and HDL-C). These findings suggest that while both agents provide systemic benefits, naringin may offer superior targeted neuroprotective effects, making it a promising candidate for the management of DN [37]. A summary of the molecular pathways of diabetic nerve injury alongside the protective roles of naringin and glimepiride is illustrated in Figure 3.

In summary, the study highlights the therapeutic potential of naringin in the management of diabetes and its complications, comparing it with glimepiride. Both compounds were effective in improving BW, glycemic status, pain sensitivity, lipid profile, neuroinflammation, and oxidative stress in diabetic rats. Notably, naringin exhibited more significant anti-inflammatory and antioxidant effects. These findings suggest that naringin could be a valuable addition to diabetes treatment, offering benefits beyond glycemic control, such as protection against neuropathy, dyslipidemia, and oxidative damage.

A limitation of this study is that it didn’t thoroughly investigate all the molecular mechanisms of naringin’s mitigating effects in DN; more in-depth research on its detailed mechanisms of action is needed. Also, further research utilizing nerve conduction velocity and molecular signaling assays is warranted to fully elucidate the underlying mechanisms of action. Furthermore, the present study utilized whole-brain homogenate for biochemical quantification. While this provides a global assessment of oxidative stress and inflammation, it may dilute region-specific variations. Since areas such as the hippocampus and cerebral cortex are known to be particularly vulnerable to diabetic metabolic insults, future studies should employ regional dissection to further refine our understanding of naringin’s site-specific neuroprotective mechanisms.