Proteomics Analysis of the Protective Effects of Hesperetin on Coronary Artery injury in Streptozotocin-Induced Type 1 Diabetic Rats


 Background: Type 1 and type 2 diabetes both cause damage to the cardiovascular system. Hesperetin, a medicinal product found in foods, has been shown to have various cardioprotective effects. However, the effects of this compound on diabetes-related cardiovascular damage have not been evaluated.Methods: In this study, we aimed to investigate the protective effects of hesperetin on the coronary artery in diabetic rats and to explore its effects on the changes in critical proteins in the coronary artery using proteomics analysis. Results: Hesperetin alleviated coronary artery injury and modulated the expression of various proteins, including S100A8 and S100A9, which functioned in Toll-like receptor 4 binding, Toll-like receptor binding, and RAGE receptor binding. Pathways altered by hesperetin included type I diabetes mellitus, cell adhesion molecules, antigen processing and presentation, and interleukin-17 signaling pathway. Conclusions: In this study, we constructed a protein map of SD rats with type 1 diabetes treated with hesperetin, and found significant changes in three important proteins, S100A8, S100A9 and KNG1.Our findings provided important insights into further studies of the cardiovascular protective effects of hesperetin.


Introduction
Diabetes is a common endocrine metabolic disease. The prevalence of diabetes has increased rapidly in the last 3 years, making diabetes one of the most common non-communicable diseases worldwide.
According to the ninth edition of the Diabetes Atlas released by the International Diabetes Federation in 2019, the global prevalence of diabetes is expected to increase to 10.2% (578 million) by 2030 and 10.9% (700 million) by 2045 [1]. Although type 1 diabetes mellitus (T1DM) accounts for only a small proportion of the total number of cases, its incidence is also increasing [1]. Compared to the general population, patients with T1DM have a 10-fold increased risk of cardiovascular disease [2][3][4][5] and coronary artery disease is the leading cause of death in patients with T1DM [1,2,6].
The complex physiological changes associated with T1DM, including hyperglycemia [7], dyslipidemia [8], in ammation [9,10], and oxidative stress [10,11] adversely affect the cardiovascular system, leading to cardiovascular complications. The general treatment strategy involves lifestyle changes, insulin therapy, regular exercise, and glycemic control, as well as administration of hypoglycemic, lipid-lowering, and antihypertensive agents. However, the risk of cardiovascular events and death in patients with T1DM is still signi cantly higher than that in the general population [12]. Therefore, safer and more effective early interventions are needed to prevent T1DM-related cardiovascular diseases.
Hesperetin (Hst) is a natural avonoid drug candidate that is abundant in food sources, including the citrus fruits of the Rutaceae family. Hst is mainly derived from the hydrolysis of hesperidin and has multiple biological and pharmacological functions. These avonoids can exert antihyperglycemic [13], anti-oxidation [14,15], antihyperlipidemic [13], anti-atherosclerosis [16], and anti-in ammatory effects [17]. Moreover, the daily dietary intake of avonoids is associated with a reduction in the incidence of cardiovascular diseases [18,19]. For example, Hst has direct vasorelaxant effects on coronary arteries via the inhibition of L-type voltage-gated Ca 2+ channels and the enhancement of voltage-gated K + channel currents in myocytes [20]. Moreover, Hst effectively inhibits collagen and arachidonic acid-induced platelet aggregation by blocking phospholipase Cγ2 phosphorylation and cyclooxygenase-1 activity [21].
However, few studies have examined the mechanisms of Hst in the coronary artery.
Accordingly, in this study, we aimed to evaluate the protective effects of Hst on coronary artery injury in T1DM model rats. Because of di culties in comprehensively exploring the mechanisms of Hst using traditional molecular biology methods, we used proteomics to screen and analyze differentially expressed proteins and identify proteins that are critical to mediating the effects of Hst on coronary artery injury in T1DM model rats. Our ndings may establish novel targets for the development of drugs for the prevention and treatment of diabetic vascular disease.

Animals and groups
Healthy male Sprague-Dawley (SD) rats (license number: SCXK2009-001) weighing 220-280 g were provided by the Laboratory Animal Center of Shanxi Medical University. The animals were housed in separate cages at a room temperature of 20-25°C and relative humidity of 50-65% under a 12-h lightdark cycle and given free access to water and food. In total, 50 SD rats were divided into control (n = 14) and model groups (n = 36); seven rats died during the modeling process. After successful modeling, rats were randomly divided into the T1DM group (n = 14) and Hst group (n = 15). All animal experimental procedures complied with the Experimental Animal Ethics Committee of Shanxi Medical University.

Drug treatment
After fasting for 12 h, all rats, except those in the control group, were intraperitoneally injected with 1% streptozotocin (STZ; Sigma, USA) dissolved in citrate buffer (pH 4.2-4.5) at a dose of 65 mg/kg. Control rats were injected with the same volume of citrate buffer. After 3 days, blood glucose was measured via the tail vein, and rats with a blood glucose level exceeding 16.7 mM for more than 1 week were considered as having T1DM. Rats in the Hst group were then intragastrically administered 100 mg/kg/day Hst (Sigma) dispersed in 0.1% sodium carboxymethyl cellulose for 4 weeks, starting at 2 weeks after the STZ injection. The control and T1DM groups were intragastrically administered an equal amount of 0.1% sodium carboxymethylcellulose.

Hematoxylin and eosin (HE) staining
At the end of the experiment, rats in each group were anesthetized, their chest was opened, and the heart was removed and placed into a beaker containing PSS (pH 7.4) solution in an environment saturated with a 95% O 2 and 5% CO 2 mixture at 4°C. After routine treatment, the hearts of three rats in each group were stained using HE dye solution (Servicebio, China), observed using microscopy (DM2500; Leica, Germany), and photographed using Leica Application Suite X software (LAS X).

Preparation of proteomic vascular samples
The hearts were removed from the beaker and xed in a Petri dish with pins. After nding the coronary arteries using an anatomical microscope (Phenix, China), they were separated by carefully removing the muscle tissue around the blood vessels using surgical microscissors and forceps. The vascular specimens were placed in a cryotube, rapidly frozen in liquid nitrogen, and stored in a freezer at -80°C.

TMT-labeled quantitative proteomics
Protein sample preparation Vascular samples were ground into a powder in liquid nitrogen and transferred to a 5-mL centrifuge tube. Then, four volumes of lysis buffer (8 M urea, 1% protease inhibitor, 3 μM TSA, 50 mM NAM) was added to the cell powder, followed by sonication three times on ice using a high-intensity ultrasonic processor (Scientz, China). After centrifugation at 4°C and 12000 × g for 10 min, the supernatants were collected, and the protein concentration was determined using a BCA kit (Beyotime, China).

Trypsin digestion
For digestion, the protein solution was reduced with 5 mM dithiothreitol for 30 min at 56°C and alkylated with 11 mM iodoacetamide for 15 min at 25±2 ℃in the dark. The urea concentration of the protein sample was diluted to less than 2 M. Trypsin was added at a mass ratio of 1:50 and 1:100 (trypsin:protein) for the rst digestion overnight at 37°C and the second 4-h digestion, respectively.

TMT labeling
After trypsin digestion, peptides were desalted using a StrataXC18 SPE column (Phenomenex) and freeze-dried in a vacuum. Peptides were dissolved in 0.5 M TEAB and labeled with a TMT kit (Thermo, USA) according to the manufacturer's instructions. Brie y, the labeled reagent was thawed and dissolved in acetonitrile, mixed with peptides, and incubated at room temperature for 2 h. The peptide mixtures were pooled, desalted, and freeze-dried in vacuum. Three technical replicates were carried out per sample, and the samples were labeled as follows: control group, 126, 127C, 128N; T1DM group, 128C, 129N, 129C; Hst group, 130N, 130C, 131.
Fractionation using high-performance liquid chromatography (HPLC) The peptides were fractionated using high pH reverse-phase HPLC using an Agilent 300Extend C18 column (5 μm particles, 4.6 mm ID, 250 mm length). Brie y, peptides were rst separated using a gradient of 8-32% acetonitrile (pH 9.0) over 60 min into 60 fractions. Then, the peptides were combined into nine fractions and freeze-dried in vacuum.

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis
The peptides were dissolved with LC mobile phase A (0.1% formic acid and 2% acetonitrile) and directly loaded onto a reversed-phase column (15 cm length, 75 μm ID). The gradient comprised an increase from 8% to 20% mobile phase B (0.1% formic acid and 90% acetonitrile) over 50 min, 20% to 35% in 35 min, and increasing to 80% in 3 min, then held at 80% for the last 3 min, all at a constant ow rate of 400 nL/min using an EASY-nLC 1000 UPLC system.
After separation using an ultra-high-performance liquid phase system, the peptides were injected into the NSI ion source for ionization and then analyzed using Orbitrap Fusion Lumos MS. The applied ion source voltage was 2.0 kV, and the scan range of the rst-level MS was set to m/z 350-1550 with 60,000 resolution; the second-level MS was set to m/z 100 with 30,000 resolution. To improve effective utilization of the mass spectrum, the automatic gain control was set at 5E4, the signal threshold was 50000 ions/s, the maximum injection time was 70 ms, and the dynamic exclusion time of the tandem MS scan was 30 s to avoid repeated scanning of the peptide precursors.
Database search LC-MS/MS raw data were processed from the UniProt Rattus database concatenated with a reverse decoy database and a common pollution database using Maxquant (v.1.5.2.8). The parameters were set as follows: algorithm, trypsin; maximum missed cleavages, 2; minimum peptide length, 7 amino acid residues; maximum modi cation number, 5. The mass error tolerance values of the precursors in the rst and main search were 20 and 5 ppm, respectively, and the second fragment tolerance was 0.02 Da.
Carbamidomethyl on Cys was speci ed as a xed modi cation. Variable modi cations were oxidation on Met and N-terminal acetylation of protein. The quanti cation type was TMT-10plex. The false discovery rate was set to 1%.

Gene Ontology (GO) annotations
The GO annotation proteome was derived from the UniProt-GOA database (https://www.ebi.ac.uk/GOA/). First, we converted the identi ed protein IDs to UniProt IDs and then mapped the proteins to GO IDs. If some identi ed proteins were not annotated by the UniProt-GOA database, InterProScan software was used to annotate the functions of the proteins based on the protein sequence alignment method. Then, proteins were classi ed into biological process, cellular component, and molecular function categories. For each category, two-tailed Fisher's exact tests were used to evaluate the enrichment of differentially expressed proteins. GO categories with corrected p values < 0.05 were considered signi cant.

Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation
The KEGG (https://www.genome.jp/kegg/pathway.html) database was used to annotate protein pathways. First, the KEGG online service tool KAAS was used to annotate protein, followed by mapping the annotation result of the KEGG pathway database using KEGG online service tools and KEGG mapper. Wolfpsort (https://www.genscript.com/psort/wolf_psort.html) was used to predict subcellular localization. For domain annotation, the identi ed protein domain functional descriptions were annotated using InterProScan and the InterPro domain database (http://www.ebi.ac.uk/interpro/), which integrates diverse information about protein families, domains, and functional sites. Lastly, the KEGG database was used to identify enriched pathways using two-tailed Fisher's exact tests. KEGG pathways with corrected p values of less than 0.05 were considered signi cant.

Protein-protein interaction network
All differentially expressed protein database accessions or sequences were searched against the STRING database (v. 11.0) for protein-protein interactions.

Western blot analysis
Coronary artery tissues of rats were ground in RIPA lysis buffer and protease inhibitor (phenylmethylsulfonyl uoride) using an MP FastPrep-24 5G rapid sample preparation instrument (MP, USA). The precipitate was gently shaken for 30 min on a shaker and removed by centrifugation for 20 min at 4°C and 13000 × g, and the protein concentration was determined using a BCA kit (Boster, China). The samples were diluted to the same concentration, mixed with 5× loading buffer, boiled at 100°C for 5 min, cooled to room temperature, and stored at -20°C until use. The proteins were then separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis on 12% gels and transferred to polyvinylidene di uoride membranes. The membranes were blocked at room temperature for 2 h with 5% skim milk dissolved in TBST, washed with TBST three times for 10 min each, and incubated with the following antibodies overnight on a shaker at 4℃: anti-β-actin (1:5000 dilution; Bioworld, China), anti-Kng1 (1:1000 dilution; ABclonal, China), anti-S100A9 (1:1000 dilution; ABclonal), and anti-S100A8 (1:1000 dilution; ABclonal). The membranes were washed three times with TBST for 10 min each and incubated with horseradish peroxidase-labeled goat anti-rabbit IgG (1:10000 dilution; Boster) on a shaker at room temperature for 1 h. After washing the membranes with TBST, an appropriate amount of ultra-sensitive ECL Ready-to-use Substrate (Boster) was added, and the membranes were exposed to a ChemiDoc MP Imaging System (Bio-Rad Laboratories, USA).

Statistical analysis
Statistical analysis was performed using SPSS software (version 26.0). The results were compared using a one-way analysis of variance followed by least signi cant difference post-hoc tests. All data are expressed as means ± standard deviations and P < 0.05 was considered statistically signi cant.

Results
Hst attenuated STZ-induced weight loss and hyperglycemia in T1DM model rats At the end of the experiment, body weight was signi cantly reduced in T1DM rats compared to control rats (Fig. 1a), whereas blood glucose was markedly increased (Fig. 1b). Treatment with Hst for 4 weeks attenuated weight loss and hyperglycemia in STZ-induced T1DM rats (Fig. 1a, b).

Histological examination of the coronary artery in rats
To evaluate the e cacy of Hst in the histology of the coronary artery under STZ-induced conditions, we used HE staining to examine the morphological structure of the rat coronary artery. The coronary arteries of control rats were clearly strati ed; the intima was smooth and at, and the vessel wall was not thickened (Fig. 2a). In contrast, the coronary arteries of STZ-induced T1DM rats showed a disordered arrangement of endothelial cells, proliferated smooth muscle cells, thickened vessel walls, and narrowed lumen (Fig. 2b). After Hst treatment, the coronary artery wall was thickened, but pathological changes in STZ-induced rats were alleviated (Fig. 2c).

Analysis of differentially expressed proteins using TMT
In order to further explore the critical proteins involved in mediating the effects of Hst on the coronary artery in T1DM rats, we analyzed differentially expressed proteins using TMT. Peptides digested by trypsin were analyzed using high-resolution MS, and the data were evaluated using various known bioinformatics databases. Most peptides contained 7-20 amino acids, consistent with trypsin enzymatic hydrolysis and HCD fragmentation (Fig. 3a). Theoretically, proteins with higher molecular weights can produce more enzymatic fragments, and more peptides need to be identi ed from a large protein to achieve the same coverage. The lengths of the identi ed peptides met the requirements for quality control (Fig. 3b). We used principal component analysis to evaluate the quantitative repeatability of protein identi cation. Closer clusters of repeated samples indicated better quantitative repeatability (Fig. 3c). When the p value was less than 0.05, changes in differential expression exceeded 1.2 as the threshold for signi cant upregulation or less than 1/1.2 as the threshold for signi cant downregulation (Fig. 3d).
Wolfpsort was used to analyze the subcellular localization of differentially expressed proteins. As shown in Fig. 4d, among the 69 differential proteins, 25 were localized in the cytoplasm, 16 were localized in the extracellular matrix, 16 were localized in the nucleus, ve were localized in the mitochondria, two were localized in both the nucleus and cytoplasm, two were localized in the plasma membrane, and the remaining three were localized in the endoplasmic reticulum, cytoskeleton, and peroxisome, respectively.
As shown in Fig. 4e, we also analyzed the clusters of orthologous groups of differentially expressed proteins. There were two RNA processing and modi cation proteins; two chromatin structure and dynamics proteins; ve energy production and conversion proteins; one cell cycle control protein; one cell division and chromosome partitioning protein; one translation protein; one ribosomal structure and biogenesis protein; two transcription proteins; two replication, recombination, and repair proteins; one cell wall/membrane/envelope biogenesis protein; three post-translational modi cation, protein turnover, and chaperone proteins; two signal transduction mechanisms proteins; one intracellular tra cking, secretion, and vesicular transport protein; ve cytoskeleton proteins; nine general function prediction proteins; and two unknown function proteins.
Functional enrichment of differentially expressed proteins in the Hst/T1DM groups Based on functional annotations, we carried out functional enrichment analysis using GO and KEGG analyses to clarify changes in the differentially expressed proteins. As shown in Fig. 5a, differentially expressed proteins were mainly involved in leukocyte aggregation, leukocyte cell-cell adhesion, oxygen transport, gas transport, isoprenoid biosynthetic process, cardiac muscle adaptation, striated muscle adaptation, muscle hypertrophy in response to stress, positive regulation of hemostasis, and positive regulation of coagulation in BPs. For CCs, most proteins were MHC protein complexes, MHC class I protein complexes, hemoglobin complexes, and nucleosomes. Similarly, the differentially expressed proteins were involved in MFs, including Toll-like receptor 4 binding, Toll-like receptor binding, RAGE receptor binding, arachidonic acid binding, fatty acid derivative binding, long-chain fatty acid binding, fatty acid binding, oxygen transporter activity, oxygen binding, icosatetraenoic acid binding, and icosanoid binding.
The results of KEGG pathway enrichment analysis (Fig. 5b) revealed that most of the proteins were enriched in type I diabetes mellitus, viral myocarditis, cell adhesion molecules, antigen processing and presentation, and the interleukin (IL)-17 signaling pathway.

Protein-protein interaction network
The overlapping differentially expressed proteins of the T1DM/control and Hst/T1DM groups were imported into STRING for visualization of the protein-protein interaction network (Fig. 6).

Veri cation of candidate proteins differentially expressed in the coronary artery
We veri ed the abundance of the proteins KNG1, S100A9, and S100A8 in coronary arteries from each group using western blotting. Consistent with the proteomics data, all three proteins were notably upregulated in the T1DM group compared to that in the control group and were signi cantly downregulated in the Hst group compared to that in the T1DM group (P < 0.05 or P < 0.01; Fig. 7). Discussion STZ is widely used to induce diabetes in animal models and can be taken up by pancreatic β-cells. β-Cell death is induced by excessive production of reactive oxygen species, resulting in diabetic symptoms such as hyperglycemia and impaired glucose tolerance [22]. Hst can reduce blood glucose levels and blood lipids by promoting insulin secretion, positively regulating the disordered carbohydrate metabolic enzymes, and reducing the levels of liver and kidney injury markers in STZ-induced experimental rats [13]. Moreover, Hst also reduces oxidative stress caused by hyperglycemia in the pancreas and prevents toxicity induced by STZ [13]. Orallo et al. [23] con rmed that Hst may have signi cant effects on vascular relaxation in rat aortic smooth muscle by increasing the intracellular concentrations of cAMP and cGMP. Although many cardiovascular protective mechanisms of Hst have been widely reported, few studies have been conducted on diabetes-related cardiovascular diseases. Therefore, we used STZ to induce T1DM in a rat model, observed changes in the coronary artery in rats, and used proteomics-based methods to study the cardiovascular protective effects of Hst.
Our experimental results showed that Hst lowered blood glucose and ameliorated coronary artery injury in T1DM model rats. The proteomic results revealed that some of the differentially expressed proteins after Hst intervention were involved in leukocyte aggregation and leukocyte cell-cell adhesion processes in the BP category and that most of these differentially expressed proteins possessed MFs related to binding. In our subsequent analyses, we focused on the roles of S100A8, S100A9, and KNG1.
Previous studies have shown an association between chronic in ammation and the presence of cardiovascular complications in individuals with type 1 diabetes [24]. S100A8 and S100A9, members of the alarmin family and S100 family of calcium-modulated proteins, are expressed in cells of myeloid origin, particularly in monocytes and neutrophils, and have been linked with cardiovascular disease [25][26][27]. Weak expression has also been observed in vascular endothelial cells [28,29] and platelets [30]. S100A8 and S100A9 generally exist as homodimers, but preferentially form the S100A8/A9 heterodimer in the presence of Zn 2+ and Ca 2+ [31], which is an active mediator in the pathogenesis of various autoimmune and in ammatory conditions [32,33]. Damage-associated molecular patterns (DAMPs) are endogenous pro-in ammatory molecules that activate innate immunity pathways and are involved in cellular functions under normal homeostasis; these molecules are released after cell death, signaling tissue damage [34,35]. S100A8 andS100A9 have been identi ed as DAMPs that can bind to cell surface receptors, such as Toll-like receptor 4 and receptor for advanced glycation end products (RAGE) [30], leading to a pro-in ammatory cascade and accelerating the chronic in ammatory process of atherogenesis associated with diabetes [31]. Additionally, studies in animal models have demonstrated that the S100A8/A9 complex is crucial for the generation of atherosclerosis and vascular injury [36]. S100A8/A9 binds heparan sulfate proteoglycans and carboxylated glycans on endothelial cells [37,38] and triggers endothelial activation, characterized by the enhanced production of in ammatory cytokines and chemokines [39,40], increased expression of adhesion molecules [39,40], and increased platelet aggregation at the surface of the endothelium [39]. The overexpression of vascular adhesion molecules on endothelial cells enhances the invasion of monocytes into the vascular wall and eventually leads to the formation of atherosclerosis and cardiovascular disease [41]. Furthermore, endothelial cells treated with S100A8/A9 show downregulation of anti-apoptotic genes and genes responsible for the integrity of the endovascular monolayer [39,42]. Extended S100A8/A9 exposure leads to endothelial cell dysfunction and increased endothelial permeability [42]. These effects are partly mediated by RAGE [43] and exacerbated by hyperglycemia [40,44]. Two other studies have supported the use of S100A8/A9 as a predictor of initial [45] or recurrent cardiovascular events [46]. Our results showed that the expression levels of S100A8 and S100A9 in the coronary arteries of T1DM rats were signi cantly higher than those in the control group. After Hst intervention, the expression levels of S100A8 and S100A9 were signi cantly decreased. In addition, enrichment in the IL-17 pathway was detected. Therefore, we speculated that S100A8 and S100A9 may be involved in the pathogenesis of T1DM vascular disease by promoting an in ammatory response and affecting endothelial function; Hst downregulated S100A8 and S100A9 to mediate these effects.
Kininogens (KNGs) are multifunctional proteins involved in multiple pathways. These proteins participate in the generation of kinins, act as cofactors for the intrinsic coagulation system, inhibit cysteine proteases, and modulate platelet aggregation, angiogenesis, and the acute-phase response. KNG1, mainly produced by hepatocytes, is a macromolecular substance that is a crucial component of the kallikrein system. KNGs produce high-and low-molecular-weight KNGs under the action of kallikrein [47]. KNG1 is the precursor of the kallikrein-kinin system and acts as a starting substrate for clinical research [48]. Recent proteomic analysis of the aorta and kidney in T1DM model rats showed that diabetes induced KNG1 expression, and this mechanism was regulated by hyperglycemia. Additionally, insulin can reverse KNG expression by controlling blood glucose levels [49]. Our results also show an increase in KNG1 levels in the T1DM coronary arteries. Notably, the KNG1 gene was identi ed as a positional candidate gene for internal elastic lamina lesions (a new event of atherosclerosis) [50], and high levels of KNG were detected in patients with in-stent restenosis after angioplasty, indicating that these patients may exhibit increased basal activity of kinins supportive of a pro-in ammatory and atherogenic state [51]. Additional evidence demonstrates the contribution of the KNG1 gene to adiponectin levels and hypertension [52,53], which are well-established risk factors for atherosclerosis. In addition, studies conducted in animal models have shown that KNG1 inhibition can prevent cardiovascular diseases (such as myocardial infarction) by combining antithrombotic and anti-in ammatory mechanisms [54]. KNG1 is also an essential physiological and pathological factor involved in regulating blood pressure, in ammation, and cardiac function [55]; however, its role in diabetes-related cardiovascular disease is unclear. In this study, we found that KNG1 expression was increased in the coronary arteries of T1DM model rats and that Hst treatment decreased KNG1 expression. Thus, KNG1 may be associated with T1DM-related cardiovascular injury, and Hst may block vascular damage by downregulating KNG1.
we found that S100A8, S100A9, and KNG1 were involved in mediating the protective effects of Hst on coronary artery injury in T1DM model rats. However, there were limitations to this study. For example, because the coronary artery samples were small, we used mixtures of samples from each group for the experiments and detected changes in protein expression. The observed changes therefore could not be attributed to speci c rats. Therefore, further proteomic analyses of heart tissues are needed. Additionally, pharmacokinetic changes may occur after oral administration of Hst, and it is also necessary to study the metabolites of Hst. With the development of genomic, proteomic, transcriptomic, and metabolomic tools, further systematic analyses of the roles of Hst will be possible.

Conclusions
In this study, TMT quantitative proteomics was used to interpret the protective mechanism of hesperetin on coronary artery injury in rats with diabetes mellitus. We found that hesperetin can improve the weight loss and blood glucose increase of diabetes, and preliminarily found several proteins S100A8, S100A9 and KNG1 involved in the protective mechanism of hesperetin, which may be involved in the in ammatory process in the development of diabetes.      represents the log2 conversion value of the proportion of differential expressed proteins to the class identi cation proteins in this pathway. The circle color represents the enriched P value, and the circle size indicates the number of differentially expressed proteins in the pathway.

Figure 6
Page 20/20 The protein-protein interaction network of the overlapping differentially expressed proteins in the T1DM/control and Hst/T1DM groups.

Figure 7
Validation of differentially expressed proteins in the control, T1DM, and Hst groups using western blotting. (A) Representative western blots. (B-D) Protein expression levels of KNG1, S100a9, and S100a8.