A novel perspective on the amelioriating effects of catechin-carbonyl adducts on AGEs toxicity

A novel perspective on the amelioriating effects of catechin-carbonyl adducts on AGEs toxicity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article A novel perspective on the amelioriating effects of catechin-carbonyl adducts on AGEs toxicity Jia Yan, Jiangying Tan, Xingyu Zhang, Chenxu Bao, Chen Zhou, Boqian He, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8521410/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Advanced glycation end products (AGEs) are significant byproducts of the Maillard reaction and are implicated in degenerative diseases. Catechin (CC), a dietary polyphenol distributed in fruits and vegetables, inhibits AGEs formation through binding with carbonyl compounds. However, the biological role of these binding adducts remains unclear. This study first isolated the major CC-methylglyoxal (MGO) adducts using high-speed counter-current chromatography. Structural analysis confirmed it retains antioxidant phenolic hydroxyls. In food models (lactose/lysine and milk), CC-MGO significantly inhibited AGEs formation via antioxidant activity. In Caco-2 cells, CC-MGO alleviated AGEs-induced cytotoxicity. Transcriptomics revealed AGEs activated the AGE-RAGE pathway (upregulating CXCL8, CCL2), while CC-MGO counteracted toxicity by modulating PPAR and IL-17 pathways, specifically upregulating SLC27A5 and downregulating MMP1 and PCK1. These findings demonstrate that catechin not only scavenges carbonyls but also forms bioactive adducts that further suppress AGEs formation and toxicity, providing a dual mechanism for natural intervention. Biological sciences/Biochemistry Biological sciences/Chemical biology Biological sciences/Drug discovery Catechin (CC) Methylglyoxal (MGO) Advanced glycation end products (AGEs) High-speed counter-current chromatography (HSCCC) Transcriptomics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction The formation of advanced glycation end products (AGEs) occurs through the Maillard reaction (MR), a non-enzymatic condensation process involving the interaction between the carbonyl group of a reducing sugar and the free amine of a nucleic acid, protein, or lipid. AGEs have the ability to interact with the receptor of advanced glycation end products (RAGE), there by modulating a wide range of cell signalling pathways. The accumulation of AGEs in the body can lead to a wide range of health effects, including the development of diabetes 1 , cardiovascular disease 2 , neurological disorders 3 , 4 , and cancer 5 . Indeed, preventing the formation or accumulation of AGEs holds promise as an effective strategy for managing and controlling chronic health diseases associated with AGEs. Reactive carbonyl compounds (RCS), including methylglyoxal (MGO), glyoxal (GO), and 5-hydroxymethylfurfural (5-HMF), are abundantly produced during the intermediate stages of the Maillard reaction (MR) 6 . These compounds form covalent bonds with nucleophilic sites in DNA, RNA, proteins, and phospholipids through Michael addition and the Schiff base reaction. MGO, GO, and 5-HMF can react with amino acids, leading to the formation of AGEs like carboxymethyl lysine (CML), carboxyethyl lysine (CEL), and 3-deoxyglucose ketone (3-DG) 7 , 8 , which may be harmful to the body 9 . Considering that carbonyl compounds are precursors of typical AGEs, the scavenging mechanism of carbonyl compounds has become a popular and important area of research. Natural polyphenols, widely found in various sources, are known for their antioxidant, anti-inflammatory, and anti-tumor properties 10 , 11 . According to Zhang et al., there are four main mechanisms by which polyphenols inhibit the MR: scavenging of free radicals, inactivation of transition metals, formation of protein-phenolic complexes, and the capacity to trap carbonyl compounds 12 . Catechin (CC), a polyphenol constituent of daily diets, is ubiquitously distributed across diverse food systems as a key bioactive compound in plant-based nutrition. As a principal dietary polyphenol, its primary sources include green tea leaves, apple peels, berry species, and cocoa beans. As a plant polyphenols, CC potent bioactivity in scavenging free radicals and modulating nuclear NF-κB signaling pathways, thereby effectively attenuating oxidative stress and suppressing pro-inflammatory cytokine production. Chen et al. demonstrated that CC with hydroxyl groups at the C-6 and C-8 positions of the A-ring could effectively bind to MGO or GO adducts in the system, which inhibited MGO or GO-mediated protein glycosylation, thereby impeding the formation of AGEs 13 . In addition, in food processing, especially foods with baking as the main process, such as bread and biscuits, contain a large amount of AGEs. However, the generation of polyphenols-carbonyl compounds by capturing the carbonyl intermediate MG/MGO by polyphenols can effectively reduce the AGEs generated in food processing 14 – 16 . While flavonoids such as hesperidin and resveratrol can inhibit the production of AGEs by lowering plasma MG concentrations, which is thought to help overweight and obese subjects increase their metabolism and vascular health, further illustrating that different types of polyphenols may promote health through the effects of different factors on AGEs 17 . However, there are no studies demonstrating whether the adducts formed by CC-captured carbonyl compounds are detrimental to cells / the body, or if they possess beneficial activities that could further inhibit the production of AGEs or mitigate AGE-induced damage. Quercetin-containing foods can scavenge reactive aldehydes, but at the same time highly-purified adducts (Que-mono-MGO and Que-di-MGO) were found to display higher cytotoxicity than their precursor MGO and quercetin 18 . On the other hand, the studie has discovered that apigenin and phloretin effectively interacted with MGO within human umbilical vein endothelial cells (HUVECs), the resulting polyphenol-carbonyl adducts significantly reduced reactive oxygen species (ROS) production and protein expression by 30–70%, producing a significant inhibitory effect on oxidative stress and inflammation in cells 19 . Phloretin-MGO adducts were also shown to inhibit AGE-induced inflammation in endothelial cells 20 . Chen et al. reported that although rutin-MGO adducts mildly inhibited cell proliferation at high concentrations, their toxicity was much lower than that of MGO 21 . Furthermore, EGCG 22 , dietary genistein 23 , and myricetin 24 were also effective in trapping MGO to form adducts, thereby reducing AGEs production. It appears that different polyphenol-carbonyl adducts generally have different properties. However, the limited number of studies mentioned above also failed to reach consistent conclusions regarding the nature of adducts, particularly in various systems such as food systems and cellular animal models. Therefore, there is a need for continued in-depth studies on the bioactivity of CC-carbonyl adducts and their effect on the MR. At present, the production of AGEs is greatly promoted by the high-fat and high-protein animal-derived nature during thermal processing, and even increases the content of AGEs by 10–100 times compared to unheated food. Therefore, the heating simulation system of lactose and L-lysine was selected to explore the inhibitory effect of CC-MGO adduct on AGEs. Subsequently, AGEs were prepared and cell models were established to investigate the amelioration of AGEs-induced cytotoxicity by CC-MGO adducts. In the study, the CC-MGO adducts were first prepared and separated using high-speed counter-current chromatography (HSCCC) and semi-preparative liquid chromatography. Transcriptomics and reverse transcription polymerase chain reaction (RT-PCR) were employed to further elucidate the regulatory effects of CC-MGO adducts on signaling pathways. In summary, this study not only demonstrated the potential of CC-MGO adducts in resisting AGEs-induced cytotoxicity but also elucidated their possible molecular mechanisms of action. These findings provide a crucial scientific foundation for utilizing natural compounds in the prevention and treatment of AGEs-related diseases. Result and discussion Trapping capacity of three carbonyl compounds by CC As depicted in Figure 1, CC exhibited significant scavenging ability for MGO, GO, and 5-HMF. The trapping capacities of these three carbonyl compounds by CC were as follows: MGO (94.81 ± 2.68%), GO (43.09 ± 3.51%), and 5-HMF (25.34 ± 3.07%), respectively. CC showed the highest clearance of MGO, followed by GO and the lowest by 5-HMF, which was consistent with the study of Chen et al 13 . MGO reacted with the hydroxyl group of CC through addition or condensation reactions, resulting in a higher capture rate due to its greater efficiency. Structural identification of CC with MGO, GO, 5-HMF The corresponding mass spectral information identified for these three adducts under the conditions specified are shown in Table 2. As depicted in Figure 2A, CC-MGO adducts and CC mostly appeared within the 3-5 min range and were difficult to separate, while MGO itself appeared around 5-6 min. After conducting mass spectrometry analysis, four potential combined products of CC-MGO adducts with mass-to-charge ratios m/z of 361.09, 433.11, 651.16, and 723.18 were identified, which is consistent with the findings of Han et al 25 . The secondary mass spectra and potential structures of the identified reaction products are presented in Figure 2. The first adduct exhibited an ion at m/z 361.09 ([M−H] − ), corresponding to one CC molecule ( m/z 289.07) combined with one MGO molecule ( m/z 71.01). The fragment ions at m/z 343.08, 289.07, and 181.05 were identified as components of a mono CC-mono MGO adduct. The fragment at m/z 343.08 ([M−H−H 2 O] − ) resulted from the loss of a water molecule (H 2 O) from m/z 361.09 ([M−H] − ), while the fragment at m/z 289.07 ([M−H] − ) originated from CC. Additionally, the fragment at m/z 181.05 ([M−H] − ) was derived from the fragmentation of m/z 343.08 ([M−H] − ). According to Sang et al 23 , CC primarily traps active carbonyl compounds via the A-ring at the C6 or C8 position. However, mass spectrometry did not allow for differentiation between these isomers. As a result, the structural formula of one isomer is presented in Figure 2F. The second adduct exhibited an ion at m/z 433.11 ([M−H] − ), consisting of one CC molecule ( m/z 289.07) and two MGO molecules ( m/z 71.01). The fragment ions at m/z 415.10, 361.09, 343.08, and 263.06 were identified as components of a mono CC-di MGO adduct (Figure 2G). The fragment at m/z 415.10 ([M−H−H 2 O] − ) was produced by the loss of a water molecule from m/z 433.11 ([M−H] − ). At this stage, MGO was attached to both the C6 and C8 positions of CC through electrophilic substitution. Previous studies have reported that CC can undergo cross-linking reactions with MGO. The third adduct exhibited an ion at m/z 651.16 ([M−H] − ), composed of two CC molecules ( m/z 289.07) and one MGO molecule ( m/z 71.01). Fragment ions at m/z 361.09, 343.08, 289.07, 245.08, and 181.05 were identified as a di CC-mono MGO adduct (Figure 2H). The fragment at m/z 245.08 ([M−H−CH 2 -CHOH] − ) resulted from the loss of a -CH 2 -CHOH group from m/z 289.07 ([M−H] − ). The fourth adduct exhibited an ion at m/z 723.18 ([M−H] − ), consisting of two CC molecules ( m/z 289.07) and two MGO molecules ( m/z 71.01). The fragment ions at m/z 361.09, 289.07, 245.08, and 181.05 were identified as a di CC-di MGO adduct (Figure 2I). In this adduct, the carbonyl groups of MGO reacted with both CC molecules via electrophilic substitution 26 . The adducts of EGCG (epigallocatechin gallate), the major catechin in tea, with MGO have been structurally characterized and identified as 8-MGO-substituted EGCG, 6-MGO-substituted EGCG, or 6,8-di-MGO-substituted EGCG 27 . Based on this, and supported by our structural analysis of the products formed from the reaction between CC and MGO, it can be hypothesized that the formation of these adducts is primarily driven by electrophilic substitution of the MGO carbonyl group onto the aromatic ring of the catechin molecules. Since both GO and 5-HMF contain a carbonyl group, it is plausible to assume that the reaction of CC with GO and HMF may occur in a similar manner as with MGO. The structures of CC&GO adducts (CGAs) were shown in Figure 3, CGAs mostly appeared within the 3-5 min range, while GO itself appeared around 4-5 min. Mass spectrometry analysis inferred that there were three potential addition and reaction products of CC with GO. The first adduct exhibited an ion at m/z 347.08 ([M−H] − ), corresponding to one CC molecule ( m/z 289.07) combined with a GO molecule ( m/z 57.00). The fragment ions at m/z 289.07, 245.08, 205.50, 167.03, 123.04, and 109.03 were identified as part of a mono CC-mono GO adduct. The fragments at m/z 245.08 ([M−H] − ), 205.50 ([M−H] − ) and 167.03 ([M−H] − ) were from CC as previously reported. The fragments at m/z 123.04 ([M−H] − ), and 109.03 ([M−H] − ) were from the fragments at m/z 347.08 ([M−H] − ). The second adduct displayed an ion at m/z 637.15 ([M−H] − ), which was two CC ( m/z 289.07) with a GO ( m/z 57.00), and the fragment ions with m/z 347.08, 289.07, 245.08, 205.50, 167.03, 123.04 and 109.03 were identified as a di CC-mono GO adduct (Figure 3F). The third adduct displayed an ion at m/z 637.15 ([M−H] − ), which was two CC ( m/z 289.07) with two GO ( m/z 57.00), and the fragment ions with m/z 289.07, 245.08, 167.03 and 109.03 were identified as a di CC-di MGO adduct (Figure 3G). The structures of CC and 5-HMF adducts (CHAs) were shown in Figure 4, CHAs mostly appeared within the 4-5 min range, while 5-HMF itself appeared around 2 min. Mass spectrometry analysis inferred that there were two potential addition and reaction products of CC with 5-HMF. The first adduct displayed an ion at m/z 415.10 ([M−H] − ), was identified as a mono CC-mono 5-HMF adduct. The second adduct displayed an ion at m/z 541.13 ([M−H] − ), was identified as a mono CC-di 5-HMF adduct. Since CC-MGO adducts were the most straightforward to separate compared to CGAs and CHAs, MGO was selected as a representative carbonyl compound for the subsequent experiments. Establishment of a method for the preparation of CC-MGO adducts A mixture of CC-MGO adducts was obtained through HSCCC and semi-preparative liquid chromatography for separation and purification (Figure 5A). In Figure 5B, the chromatogram illustrated the semi-preparative liquid phase separation of CC-MGO adducts. The samples with four peaks in the figure were collected individually and analyzed using LC-MS/MS. It was separated that the sample was isolated at 30-35 minutes. Figure 5C presented the analysis of three sets of samples separated by HSCCC. As illustrated in Figure 5B and 5C, HSCCC proved to be more effective than semi-preparative liquid chromatography for the separation of CC-MGO adducts. Therefore, HSCCC was selected for the subsequent experiments to separate CC-MGO adducts. Antioxidant properties of CC-MGO adducts and the inhibitory effects on AGEs formation in simulation and milk food system To prepare CC-MGO adducts for further studies in simulated and real food systems (Figure 6A), it is essential to first ascertain their beneficial antioxidant properties. Indeed, both the DPPH and the ABTS+ method were valuable tools for evaluating the antioxidant potential of compounds. As presented in Figure 6B, CC-MGO adducts exhibited significant scavenging effects on both DPPH radicals and ABTS+ radicals, with the dose-dependent scavenging effects. The radical scavenging activity of phenolics primarily relied on factors such as the dissociation energy of the hydroxyl group binding, the resonance dissociation stability of the phenoxyl radical, and the site-blocking effect caused by substituents present in the aromatic ring. These characteristics significantly influenced phenolic compounds' antioxidant capacity 28 . The phenolic hydroxyl and polyhydroxyl configurations of CC have been reported as the active sites responsible for scavenging free radicals in antioxidant activity 29 . Although the formation of CC-MGO adducts alters the structure of CC, primarily affecting the A-ring as shown in Figure 2A, the key phenolic hydroxyl groups, particularly the catechol structure on the B-ring, which serves as the main site for CC’s potent radical-scavenging activity through hydrogen donation and radical stabilization 30,31 , remain intact. Therefore, the ABTS⁺ and DPPH scavenging activities observed in CC-MGO adducts are mainly attributed to the preservation and availability of these critical phenolic hydroxyl groups, with their intrinsic antioxidant capacity largely unaffected by modifications to the A-ring. Since CC-MGO adducts retained the four phenolic hydroxyl groups present in the structure of CC, it was assumed that CC-MGO adducts also maintained the antioxidant capacity of CC. Heated lactose/L-lysine simulation system and milk system were chosen to explore the inhibitory effect of CC-MGO adducts on the generation of AGEs in simulated food system. In the lactose/lysine system, MR occurred between the carbonyl group of lactose and the amino group of L-lysine. When the concentration of L-lysine was 30 mM, the CMAs began to show an inhibitory effect on the generation of AGEs in the simulated system, which may be due to the fact that the reaction of L-lysine with lactose was basically reacted completely. As depicted in Figure 6C, it was observed that CC-MGO adducts exhibited a promoting effect on the generation of AGEs in simulated food system at a concentration of L-lysine of 60 mM. Based on the structural properties of the adduct, which retained the carbonyl group of MGO, it was assumed that after the reaction of L-lysine with lactose, L-lysine could still continue to occur MR with the carbonyl group on the CC-MGO adducts, thus promoting the generation of AGEs. At an L-lysine concentration of 30 mM, CC-MGO adducts exhibited an inhibitory effect on the generation of AGEs in simulated food system, which was likely because the reaction between L-lysine and lactose had reached a state of near completion. In contrast, the MGO during the MR is much larger than the binding site of CC-MGO adducts, so the overall inhibition rate is only 20%. The inhibition of AGEs in simulated food system by CC-MGO adducts reached 50% at L-lysine concentrations of 12, 15 and 20 mM. The mechanism of inhibition of AGEs by CC-MGO adducts was hypothesized to be two pathways: (1) Carbonyl compounds were generated by oxidative reactions during the maillard reaction, e.g., direct oxidative degradation of glucose, and oxidative degradation of Schiff base during the MR 32 . The antioxidant results show that CC-MGO adducts had good free radical scavenging ability and can inhibit the formation of carbonyl compounds and AGEs during the MR by antioxidant mechanism. (2) MGO induced the formation of AGEs from amino acids or free amino acid residues in proteins, and there were still binding sites in CC-MGO adducts that were not fully reacted with MGO, so the formation of AGEs can be inhibited by capturing MGO. Our LC-MS analysis confirmed the formation of multiple CC-MGO adducts in the isolated samples, including mono-CC-mono-MGO, mono-CC-di-MGO, di-CC-mono-MGO, and di-CC-di-MGO species. Notably, the detection of mono-MGO-bound adducts (e.g., mono-CC-mono-MGO and di-CC-mono-MGO) suggests the presence of unreacted nucleophilic sites, such as the C6 and C8 positions on the catechin A-ring or free phenolic hydroxyl groups, within these adducts. This structural feature is consistent with previous findings by Liu et al 33 , who demonstrated that di-MGO-quercetin adducts retained the capacity to bind additional MGO molecules, forming tris-MGO-quercetin complexes. Based on this analogy, we propose that CC-MGO adducts, particularly those containing only one MGO moiety, may retain residual MGO-scavenging capacity through their unoccupied reactive sites. This ability to further sequester free MGO may underlie the observed suppression of AGEs formation, thereby enhancing the functional role of these adducts in mitigating glycation-related cellular damage. Since there was no significant difference between the L-lysine concentration of 20 mM and 12 mM, an L-lysine concentration of 20 mM was selected for the experiment. In order to imitate the MR triggered by milk pasteurization at 65°C for 30 minutes, an authentic milk system was established. To assess the capacity of CC-MGO adducts to impede the formation of AGEs in both contexts, varying concentrations of CC-MGO adducts were added to the lactose/L-lysine simulation system and the milk system, respectively. Figure 6D and 6F visually illustrated that the sample solution assumed a progressively more intense yellow tint as the concentration of CC-MGO adducts added prior to heating increased. This color shift could likely be attributed to the inherent yellow pigmentation of CC-MGO adducts themselves. The sample solution in the simulated system eventually turned brown as it heated up because the late stages of the MR would produce brown macromolecules, such as melanoidins compounds, which would change the color of the solution. Meanwhile, this system simulates real food processing by applying heat, which promotes the Maillard reaction between the carbonyl group of lactose and the amino group of L-lysine, resulting in increased formation of AGEs. In contrast, within the milk system, due to the irregular reflection of light caused by fat globules and protein particles, the color of the solution remained unaltered both before and after the heating procedure. The formation mechanism of AGEs was complex, and cross-linking between amino acids could produce representative AGEs such as pentosidine, argpyrimidine, crossline and vesperlysine, which were all autofluorescent. Measuring the fluorescence value could be a simple and effective way to measure the content of fluorescent AGEs, and the magnitude of the fluorescence value could measure the amount of fluorescent AGEs generated, so as to calculate the inhibition rate of CC-MGO adducts on AGEs. As illustrated in Figure 6E and 6G, it was evident that the inhibitions of AGEs, pentosidine, argpyrimidine, crossline, and vesperlysine were higher with increasing concentrations of CC-MGO adducts. The results obtained from this experiment were in agreement with the findings reported by Liu et al 33 . Notably, comparison with the positive control AG (Figure 6E, 6G, 6H, 6I, 6J) showed that 1 mM CC-MGO achieved a similar inhibition rate to 5 mM AG, confirming their strong potential to suppress AGEs formation. Inhibition of AGEs cytotoxicity by CC-MGO adducts The cell viability of MGO and CC-MGO adducts was assessed using the CCK8 assay to screen for appropriate concentrations. As depicted in Figure 7A, in the Caco-2 cell model, cell viability decreased with increasing concentrations of CC-MGO adducts and MGO. At a concentration of 50 μM, no significant difference in cytotoxicity was observed between the CC-MGO adducts and MGO, with cell viability remaining above 95%. However, as the concentration increased, notable differences emerged. At 2000 μM, the viability of Caco-2 cells in the MGO group was 78.76 ± 0.53%, whereas in the CC-MGO adduct group, it was significantly higher at 84.90 ± 2.42%. Used the concentration of the CC-MGO adducts at which Caco-2 cell viability was not lower than 80% for subsequent experiments,which was determined to be lower than 2000 μM. Figure 7B presents the alterations in free amino acids observed during the glycation process of bovine serum albumin. The free amino acid content of bovine serum albumin heated alone was notably high at 97.10 ± 4.26%, whereas the free amino acid content of the model AGEs formed after heating with MGO drastically reduced to 20.51 ± 0.08%. This substantial decrease in the relative content of amino groups in the AGEs model, compared to bovine serum albumin heated alone, suggests effective binding of the carbonyl group on MGO with the amino group on bovine serum albumin. Consequently, the successful construction of the glycation model is inferred. And the fluorescence intensity of AGEs exhibited a more pronounced decrease compared to that of natural bovine serum albumin. This phenomenon can be attributed to the close linkage or interaction between the carbonyl group in MGO and the amino acid residues in bovine serum albumin, resulting in a certain shielding effect that diminishes the overall fluorescence. Concurrently, the redshift observed in the emission wavelength of AGEs indicates an increase in the polarity of the surroundings of the amino acid residues. This shift suggests that the hydrophobic amino acids within the AGEs molecule are more exposed to the surface compared to natural bovine serum albumin, leading to a redshift in peak emission following the MR 34 . The cell viability of AGEs was assessed using the CCK8 method. As illustrated in Figure 7C, low concentrations of AGEs, such as 5 mg/mL, exhibited a minor effect on Caco-2 cell viability, yielding a viability of 85.51 ± 1.86%. However, with increasing concentrations of AGEs, a significant decrease in cell viability was observed, indicating a gradual increase in toxicity. At a concentration of 30 mg/mL, cell viability dropped close to 50%. Subsequently, at concentrations of 35 and 40 mg/mL, cell viability decreased markedly to approximately 30%, signifying intensified toxicity. Following literature guidance 35 , the AGEs concentration corresponding to 50% cell viability of Caco-2 cells was chosen for subsequent CCK8 toxicity experiments, which was determined to be 30 mg/mL. The inhibitory effect of CC-MGO adducts on the cytotoxicity induced by AGEs was assessed using the CCK8 assay. Based on the experimental results outlined above, a concentration of 30 mg/mL of AGEs was selected for this investigation. Comparative analysis with the cell viability of the control group revealed that CC-MGO adducts demonstrated an inhibitory effect on AGEs-induced cytotoxicity when its concentration was equal to or less than 500 μM. However, when the concentration of CC-MGO adducts exceeded 750 μM, both CC-MGO adducts and AGEs exhibited toxicity towards Caco-2 cells, thereby affecting cell viability. As depicted in Figure 7D, it is evident that CC-MGO adducts at a concentration of 100 μM exerted the most significant inhibitory effect on AGEs-induced cytotoxicity, resulting in a notable increase in cell viability to 135.19 ± 1.79% compared to the cellular control group adding AGEs. Conversely, with an increase in CC-MGO adducts concentration, there was a gradual decline in Caco-2 cell viability in the presence of both CC-MGO adducts and AGEs. Particularly noteworthy is the observation that at a CC-MGO adducts concentration of 2000 μM, Caco-2 cell viability plummeted to only 45.65 ± 2.56% of that observed in the control group. Based on the findings of this experiment, subsequent transcriptome analysis was conducted using AGEs at a concentration of 30 mg/mL and CC-MGO adducts at a concentration of 100 μM. These datas clearly elucidate the inhibitory effect of CC-MGO adducts on AGEs induced cytotoxicity, and provide a theoretical basis for the subsequent inhibitory mechanism of CC-MGO adducts on AGEs induced Caco-2 cytotoxicity at the transcriptional level. Mechanistic analysis of the mitigating effects of CC-MGO adducts on AGE-induced cytotoxicity. Principal component analysis (PCA) was employed to determine the first principal component (PC1) and the second principal component (PC2) of gene expression differences among each sample. As depicted in Figure 8A, minimal differences and high biological reproducibility were observed among all three parallels in the CK, AGEs, and CC-MGO adducts groups. Simultaneously, the three sample groups exhibited substantial separation from each other, indicating variability across different groups. The analysis of differentially expressed genes were presented in Figure 8B and 8C, where volcano plots depict the comparison of gene expression between different groups, namely the control, AGEs, and CC-MGO adducts groups. In our analysis, genes meeting two criteria were identified as differentially expressed: a fold change in expression greater than or equal to 2 and a significant level of expression difference less than or equal to 0.05. Due to the substantial number of differentially expressed genes between the control and AGEs groups, the fold change threshold was adjusted to 2.0. Each point on the volcano plot represents a metabolite, with significantly upregulated, downregulated, and non-significant metabolites shown in red, blue, and gray, respectively. This adjustment resulted in 1143 up-regulated genes and 697 down-regulated genes between the control and AGEs groups. For example, the downregulation of EGR1, an early growth response protein among the downregulated genes, inhibited cell proliferation and induced apoptosis. In contrast, the upregulation of CXCL8, a CXC-type chemokine, initiated the inflammatory response. Conversely, between the AGEs and CC-MGO adducts groups, there were 56 differentially up-regulated genes and 78 down-regulated genes. SLC27A5, an upregulated gene, inhibited the proliferation of hepatocellular carcinoma cells to some extent, while PCK1, a downregulated gene, was associated with the promotion of diabetes mellitus development when its levels were elevated. Figure 8D illustrates the horizontal coordinates as GO-annotated secondary classifications, while the vertical coordinate represents the number of genes corresponding to each secondary classification. Total, up-regulated, and down-regulated expressed genes are depicted in blue, red, and green, respectively. The figure categorizes the differential genes in the CK and AGEs groups based on these three ontologies. Table 3 outlines the top 10 GO functional annotations, indicating enrichment across the biological process, molecular function, and cellular component ontologies. Among these annotations, six pertain to biological processes, two to molecular functions, and two to cellular components. The differential genes involved in biological processes primarily include cellular processes, metabolic processes, biological regulation, regulation of biological processes, stimulus response, and response to stimulus. In terms of molecular functions, differential genes mainly participate in binding and catalytic activity. Regarding cellular components, differential genes are primarily associated with cells, cell parts, and cellular processes. Furthermore, differential genes related to cellular components predominantly involve cell parts. As shown in Figure 8E and Table 4, the differential genes in the AGEs and CC-MGO adducts groups were similarly categorized by the above three ontologies. Among the top 10 GO functional annotations, five were enriched in the biological process ontology, three in the cellular location ontology, and two in the molecular function ontology. Among them, the differential genes involved in biological processes mainly include cellular process, metabolic process, single-organism process, regulation of biological process, biological regulation, and bioregulation. The differential genes involved in cell location mainly include cell, cell part and organelle; the differential genes involved in molecular function mainly include binding, catalytic activity and molecular function. The genes involved in molecular function mainly include binding and catalytic activity. Based on the results of variance analysis and KEGG annotation, the clusterProfiler software was employed to identify significantly enriched KEGG pathways using a threshold of p-value < 0.05. The KEGG enrichment analysis table was then utilized to generate an enrichment bubble map, visually depicting the results of the KEGG enrichment analysis. As illustrated in Figure 8F, KEGG enrichment bubble diagrams were constructed based on the top 10 pathways enriched by KEGG. The horizontal coordinate represents GeneRatio, indicating the ratio of the number of enriched differential genes to the entry against the total number of differential genes in the functional annotation results. The vertical coordinate depicts the entries on the enrichment. The size of the dots corresponds to the number of genes involved in the enrichment, while the color of the dots represents the p-value, with lower values indicating greater significance. Studies have demonstrated that the initiation of diabetes and its complications by AGEs typically involves a signaling cascade mediated by RAGE 36 . Upon binding of AGEs to their receptor RAGE, RAGE transmits signals into the cell and mediates downstream cell signaling pathways. Binding of oligopeptide-AGEs to RAGE-V initiates downstream cell signaling, and four RAGE-mediated pathways have been identified: Ⅰ. Janus kinase (JAK) and signal transducers and activators of transcription (STAT) pathway 37 . Ⅱ. Phosphatidylinositide 3-kinases (PI3-K)-protein kinase B (AKT) pathway 38 . Ⅲ. Mitogen-activated protein kinases (MAPK) and extracellular regulated protein kinases (ERK) pathways 39 . Ⅳ. Reduced coenzyme II (nicotinamide adenine dinucleotide phosphate (NADPH)-ROS pathway 40 . According to Figure 8F and Table 5, various degrees of significant differences were observed in the four signaling pathways mentioned, as enriched in the KEGG signaling pathway analysis of the AGEs group compared to the control. Additionally, several RAGE-mediated inflammatory signaling pathways, such as the NF-κB signaling pathway and the IL-17 signaling pathway, exhibited notable differences. Particularly noteworthy is the enrichment of the AGE-RAGE signaling pathway in the differential analysis, consistent with previous findings indicating that AGEs induce cytotoxicity in Caco-2 cells through binding to RAGE. This binding triggers downstream cellular signaling pathways, leading to the activation of inflammatory factors, nuclear transcription factors, and other molecules 11 . Therefore, the AGE-RAGE signaling pathway in diabetic complications emerges as a pivotal pathway requiring investigation in subsequent experiments. Furthermore, KEGG enrichment analysis identified 12 significant differential genes in the AGE-RAGE signaling pathway. Among these, 7 genes were significantly up-regulated, namely CXCL8, CCL2, SERPINE1, IL1A, PIK3CD, NOS3, and AKT3, while 5 genes were significantly down-regulated, namely EDN1, EGR1, AGT, TGFB2, and COL4A1. According to Figure 8G and Table 6, the signaling pathways enriched by KEGG in the CC-MGO adducts and AHEs groups were mainly the following ten. Among them, PPAR and IL-17 signaling pathways are the major inflammatory pathways 41 . While AGEs induce cytotoxicity mainly by binding to their receptor RAGE and activating downstream cell signaling, thus inducing overexpression of inflammatory factors and triggering cytotoxicity. Therefore, we hypothesized that CC-MGO adducts alleviate AGEs-induced cytotoxicity by affecting PPAR and IL-17 signaling pathways. Based on the differential genes enriched by KEGG, we found that SLC27A5 was up-regulated and PCK1 and MMP1 genes were significantly down-regulated in the PPAR pathway, while the differential genes MMP1 and FOSB were both down-regulated in the IL-17 signaling pathway. Subsequent RT-PCR experiments were performed to further validate our transcription results. To validate the involvement of the AGE-RAGE signaling pathway in AGEs toxicity, as suggested by KEGG enrichment, we performed RT-qPCR analysis comparing the expression of key pathway genes between the Control (CK) and AGEs groups. In the RT-PCR experiments(Figure 9A) depicted in Figure 8C, the expression levels of CXCL8, CCL2, SERPINE1, IL1A, PIK3CD, NOS3, and AKT3 were found to be up-regulated in the AGEs group, whereas the expression of EDN1, EGR1, AGT, and TGFB2 was down-regulated. Notably, IL1A, an inflammatory factor belonging to the interleukin family, is known to regulate inflammation effectively. The elevated expression of IL1A suggests that the addition of AGEs leads to increased levels of inflammatory expression in Caco-2 cells, contributing to cytotoxicity 42 . Moreover, the decreased expression of EGR1, an essential early growth response protein that controls tumor cell growth and proliferation, following incubation with AGEs indicates the inhibition of normal cell growth, potentially leading to apoptosis 43 . The expression patterns of other genes also suggest their relevance to AGEs-induced cytotoxicity. Overall, AGEs can induce Caco-2 cytotoxicity by affecting the AGE-RAGE signaling pathway. To validate the predicted involvement of the PPAR and IL-17 signaling pathways in CC-MGO adducts-mediated cytoprotection (based on GO/KEGG), we performed RT-qPCR analysis comparing the expression of key genes within these pathways between the AGEs group and the group co-treated with AGEs and CC-MGO adducts. As depicted in Figure 9D, SLC27A5 exhibited significant up-regulation, whereas MMP1, PCK1, and FOSB expression was markedly decreased in Caco-2 cells following pre-incubation with CC-MGO adducts. The observed up-regulation of SLC27A5 is noteworthy, considering its significant under-expression in hepatocellular carcinoma tissues. Conversely, high-level expression of PCK1 has been linked to diabetes promotion 44 , overexpression of MMP1 is associated with tumorigenesis and metastasis 45 , and increased FOSB expression has been implicated in gastric carcinogenesis 46 . These findings suggest that CC-MGO adducts may further alleviate AGEs-induced cytotoxicity by modulating the expression of these genes and influencing the activation of PPAR and IL-17 pathway transduction (Figure 9B). Transcriptomic analysis indicated that AGEs-induced cytotoxicity was mainly mediated by the AGE-RAGE signaling pathway, with significant upregulation of inflammatory genes such as CXCL8 and CCL2 (Figure 9C). In contrast, CC-MGO adducts exerted protective effects via distinct mechanisms, as KEGG enrichment identified PPAR and IL-17 pathways (Figure 9D). Notably, upregulation of SLC27A5 and PCK1 suggested PPAR activation, enhancing metabolic and antioxidant capacity, while downregulation of MMP1 and FOSB implied suppression of IL-17-mediated inflammation. Since PPAR activation antagonizes NF-κB signaling, a key downstream effector of RAGE, these results indicate that CC-MGO adducts do not simply reverse AGEs-induced changes but instead activate complementary protective pathways. Collectively, the findings suggest that CC-MGO adducts mitigate AGEs toxicity by enhancing metabolic resilience and limiting inflammatory responses through PPAR and IL-17 signaling, thereby counteracting RAGE-driven pathological processes including oxidative stress and metabolic disruption. KEGG analysis revealed significant enrichment of the AGE-RAGE signaling pathway, with key genes (CXCL8, CCL2, IL1A, SERPINE1, PIK3CD, NOS3, AKT3, EDN1, EGR1, AGT, TGFB2) upregulated, highlighting RAGE activation as the main driver of AGEs-induced cytotoxicity in Caco-2 cells. These genes regulate inflammation, oxidative stress, endothelial dysfunction, and fibrosis—hallmarks of RAGE signaling. Although RAGE protein levels and downstream phosphorylation (e.g., NF-κB, MAPKs) were not directly assessed, the cytoprotective effects of CC-MGO adducts suggest functional activity despite limited intestinal absorption. Protection may arise from: Ⅰ. direct scavenging of reactive carbonyl species (e.g., MGO) and ROS in the intestinal lumen or at the cell surface, thereby reducing initial cellular damage 19,47 ; Ⅱ. inhibition of receptor-mediated signaling pathways, such as AGE-RAGE interactions; and Ⅲ. activation of intracellular protective mechanisms, such as the Nrf2 antioxidant pathway, potentially by a small fraction of absorbed CC-MGO adducts or their intracellularly generated active components (e.g., liberated CC or its metabolites), as supported by our transcriptomic data. Conclusion This study identified CC adducts with MGO, GO, and 5-HMF using LC-MS/MS, and successfully isolated CC-MGO adducts by HSCCC. Structural analysis revealed that CC-MGO forms via electrophilic substitution between MGO carbonyl groups and the CC benzene ring, while retaining phenolic hydroxyls and antioxidant properties. Antioxidant assays and food models (lactose/lysine, milk) confirmed that CC-MGO significantly inhibited AGEs formation. In Caco-2 cells, CC-MGO alleviated AGEs-induced cytotoxicity. Transcriptomic and RT-PCR analyses showed that AGEs toxicity involved AGE-RAGE signaling (e.g., CXCL8, CCL2, SERPINE1, IL1A), while CC-MGO mitigated damage through modulation of PPAR and IL-17 pathways (e.g., SLC27A5 upregulation, MMP1 and PCK1 downregulation). Overall, CC inhibits AGEs not only by trapping carbonyls but also via bioactive CC-MGO adducts, which further suppress AGEs toxicity in food and cellular systems. These findings provide a scientific basis for developing natural inhibitors of AGEs. Materials and methods Materials CC, MGO (40% aqueous solution, w/w), GO (40% aqueous solution, w/w), 5-HMF (≥ 95%), lactose (comprising 30% α-lactose and 70% β-lactose). L-lysine (98%), o-phenylenediamine (OPD, ≥ 98%) and 2,3-dimethylquinoxaline (DQ, ≥ 97%) were sourced from Shanghai Maclean Biochemical Technology Co. Milk was provided by Inner Mongolia Meng Niu Dairy (Group) Co., Ltd. Penicillin (100 U/mL), streptomycin (100 ug/mL) were acquired from Greiner. DMEM medium was made available from Hyclone. Fetal Bovine Serum was obtained from Gibco. Cell Counting Kit-8 was purchased from Shanghai Beyotime Biotechnology Co.. The Caco-2 cells were kindly provided by the Oil Crops Research Institute (OCRI) of the Chinese Academy of Agricultural Sciences, Wuhan, Hubei Province, China. The preparation of CC-MGO adducts Measurement of MGO, GO and 5-HMF trapping capacity by CC The trapping capacities of MGO, GO, and 5-HMF by CC (5 mM) were assessed in triplicate according to a published method with modifications 48 . All solutions were prepared in 50 mM PBS (pH 7.4). Reaction mixtures (0.5 mL total volume) contained either MGO, GO, or 5-HMF (0.25 mL of 5 mM) with an equal volume of either PBS (control groups) or CC (5 mM, sample groups). After incubation (37°C, 1 h) and quenching on ice, 0.125 mL of OPD (20 mM) and the internal standard DQ (5 mM) were added. Derivatization proceeded for 30 min (MGO/GO) or 5 min (5-HMF). Samples were then filtered (0.22 µm) and analyzed by HPLC under conditions adapted from Wu et al 49 for MGO/GO and Teixidó E et al 50 for 5-HMF. Structural identificationof CC adducts with MGO, GO, and 5-HMF The adduct samples were diluted 100-fold, and then they underwent detection using LC-MS/MS 51 . The mass spectra were acquired using Electrospray Ionization (ESI) in negative ion mode. The capillary voltage was maintained at 3 kV, and the fragment voltage was set at 70 V. The atomization pressure was set to 40 psi, and the dry gas temperature was set at 300°C. The mass spectrometry ion range was scanned from 50 to 800 m/z . Effect of separation methods on the relative content of CC-MGO adducts Semi-preparative liquid chromatography The semi-preparative liquid phase was prepared using the method described by Liu et al. with some modifications. The column was Diamonsil TM-C18 (4.6×200 mm, 5 µm). Mobile phase A was used 0.1% formic acid aqueous solution, and Mobile phase B was absolute methanol. The gradient elution process was used: 10% B at 0 min, 15% B at 2 min, 20% B at 5 min, 20% B at 15 min, 25% B at 17 min, 25% B at 21 min, 90% B at 22 min, 90% B at 24 min, 10% B at 28 min, and 10% B at 40 min. The target product was monitored at 273 nm and collected for structural identification and subsequent testing. High-speed counter-current chromatography The HSCCC was prepared using the method described by Bito et al. with some modifications 52 . The solvent system selected for pre-separation was n-butanol-ethyl acetate-water (1:14:15, v/v/v). Following the degassing treatment, the reaction mixture of CC and MGO was subjected to vacuum freeze-drying, as described previously, to obtain the crude sample. Before injection, the circulating water bath was turned on, and the temperature was set to 25℃. The flow rate of the stationary phase was set to 5 mL/min. The rotational speed was 900 r/min. The mobile phase was pumped into the system at a 1 mL/min flow rate. The detection wavelength was set at 280 nm. Impact of CC-MGO adducts on AGEs formation in simulated food system Antioxidant analysis of CC-MGO adducts DPPH free radical scavenging ability The DPPH free radical scavenging capacity of CC-MGO adducts was determined according to the method of Wu et al. with some modifications 53 . The antioxidant activity of each sample was calculated as follows. Preparation of DPPH detection samples: Prepare CC-MGO adducts samples with deionized water at the following concentrations: 1, 2, 3, 4, and 5 mM. Mix CC-MGO adducts (0.2 mL) or 0.2 mL deionized water (blank) at different concentrations with 3.8 mL of 0.1 mM DPPH ethanol solution. Among them, A represented the absorbance at 517 nm of the mixture containing the CC-MGO adducts and DPPH-ethanol solution. Ab represented the absorbance at 517 nm of the CC-MGO adducts alone (without DPPH). A0 represented the absorbance at 517 nm of the DPPH-ethanol solution. ABTS + radical scavenging ability The ABTS⁺ radical scavenging capacity was evaluated using a reported method 53 . The ABTS⁺ stock solution was generated by reacting equal volumes of 7.4 mM ABTS and 2.6 mM potassium persulfate in the dark at room temperature for 12 h. The working solution was then diluted with deionized water to an absorbance of 0.70 ± 0.02 at 734 nm. Antioxidant activity was calculated as follows: Among them, A represented the absorbance at 517 nm of the sample with ABTS + . A 0 represented the absorbance at 517 nm of ABTS + . Effect of lysine concentration on AGEs inhibition by CC-MGO adducts in simulated food systems Lactose (60 mM) and L-lysine at different molar ratios (lactose:lysine = 1:1 to 5:1) were prepared in 0.02 M PBS (pH 7.4). The CC-MGO adducts solution (5 mM) was added at a 1:1:1 volume ratio with lactose and lysine solutions. Control groups used PBS instead of the adduct solution. After vortexing, samples were heated at 98 ± 2°C for 1 h. Fluorescence was measured at Ex/Em = 370/440 nm. Influence of CC-MGO adducts on AGEs formation in simulated and milk food systems The influence of CC-MGO adducts on AGEs formation was evaluated in both simulated and milk systems. In the simulated system, lactose (60 mM) and L-lysine (20 mM) were incubated with CC-MGO adducts or aminoguanidine hydrochloride (AG) (1–5 mM) in PBS. In the milk system, CC-MGO or AG (1–5 mM) was directly added. Blank controls received no additives. The simulated system was processed using the aforementioned method, and the milk system was heated at 65 ± 2°C for 30 min 54 . After reaction, fluorescence of specific AGEs (AGEs, pentosidine, argpyrimidine, crossline, vesperlysine) was measured 55 . Inhibitory effect of CC-MGO adducts on AGEs induced cytotoxicity Cell viability assay of MGO and CC-MGO adducts The cytotoxicity of MGO and CC-MGO adducts was assessed using a CCK-8 assay. Cells were seeded in 96-well plates at 1 × 10⁴ cells/well and cultured for 24 h. Filter-sterilized samples were diluted in complete medium to concentrations ranging from 50 to 2000 µmol/mL. Then, 100 µL of each sample was added to the wells, with six replicates per concentration, using medium as the negative control. After 24 h of incubation, 10 µL of CCK-8 solution was added to each well and incubated for another 1.5 h at 37°C. Absorbance was measured at 450 nm using a microplate reader (Thermo, USA). Cell viability was calculated as follows: where A sample is the absorbance of the sample, A control is the absorbance of the negative control (cells with medium), and A blank is the absorbance of the solvent blank (medium only). Role of CC-MGO adducts on AGEs-induced cytotoxicity AGEs were generated using bovine serum albumin and MGO, and characterized by free amino group content and fluorescence spectroscopy 56 . Cytotoxicity was evaluated via CCK-8 assay. Various concentrations of AGEs (5–40 mg/mL) were tested to establish a cytotoxic model. To assess protection, cells were pre-treated with CC-MGO adducts for 12 h, washed with PBS, and then exposed to AGEs for 24 h. Cell viability was measured using the CCK-8 assay, with blank (untreated) and control (AGEs-only) groups included for comparison. Transcriptome sequencing Transcriptome sequencing was performed on extracted tissue RNA. Poly(A) mRNA was enriched using oligo (dT) beads and fragmented. cDNA was synthesized from the fragmented mRNA and PCR-amplified to construct sequencing libraries. After quality control, reads were aligned and analyzed for gene expression, variants, novel transcripts, SNPs, and gene structure optimization. Differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. RT-PCR Caco-2 cells were cultured in a 6-well plate for 24 hours following treatment with diluted digestive fluid (50-fold dilution) that had been filtered using a centrifugal ultrafiltration tube to remove digestive enzymes. Reverse transcription was performed with the first-strand cDNA synthesis kit. The reverse transcription process involved pre-denaturation at 95°C for 3 min, denaturation at 95°C for 10 s, annealing at 58°C for 30 s, extension at 72°C for 30 s, and 40 cycles of amplification. Threshold cycle (CT) values were utilized to calculate mRNA expression. For each sample, the ∆CT(sample) value was determined by calculating the difference between the CT value of the target gene and the CT value of the β-actin inner reference gene. Expression levels relative to the control were estimated by calculating ∆∆CT (∆CT(sample)- ∆CT(control)) and then using the 2 −∆∆CT method 57 . The primer design is shown in Table 1 . Data analysis The data obtained from the experiments were subjected to statistical analysis using IBM SPSS Statistics 21 software. The results were then expressed as the mean ± standard deviation. Comparisons of means between multiple groups were performed by one-way one-way ANOVA (OneWay ANOVA), and multiple comparisons between groups were performed using Duncan's test if there was a significant difference between groups (p < 0.05). Plotting was done using Origin 8.0 software. Abbreviations ABTS: 2,2'-Azinobis- (3-ethylbenzthiazoline-6-sulphonate); AGEs: Advanced glycation end products; BSA: Bovine albumin; CC: Catechin; CHAs: CC&5-HMF adducts; CCK8: Cell Counting Kit-8; CEL: NƐ-carboxyethyl lysine; CGAs: CC&GO adducts; CML: NƐ-carboxymethyl lysine; DPPH: 1,6- Bis (diphenylphosphino) hexane; DQ: 2, 3-Dimethylquinoxaline; GO: Glyoxal; HSCCC: High-speed counter- current chromatography; MGO: Methylglyoxal; MR: Maillard reaction; OPD: O-Phenylenediamine; RCS: Reactive carbonyl species; ROS: Reactive oxygen species; 5-HMF: 5-hydroxymethylfurfural. Declarations CRediT authorship contribution statement Jia Yan : Conceptualization, visualization and writing – review & editing. Jiangying Tan : Data curation and writing original draft. Xingyu Zhang : Investigation and methodology. Chenxu Bao : Investigation and visualization. Chen Zhou : Conceptualization and methodology. Boqian He : Conceptualization and data curation. Yinxin Li : Conceptualization and methodology. Baiyi Lu : Supervision. Lianliang Liu : Supervision. Fan Yi : Supervision. Qian Wu : Conceptualization, funding acquisition and supervision. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data Availability Data will be made available on request. 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Inhibition of advanced glycation endproducts formation by lotus seedpod oligomeric procyanidins through RAGE-MAPK signaling and NF-κB activation in high-AGEs-diet mice. Food Chem Toxicol 156 , 112481, doi:10.1016/j.fct.2021.112481 (2021). Tables Table 1. Real-time quantitative PCR primer design Gene name Primer base design EDN1-F TCTCTCTGCTGTTTGTGGCTTGC EDN1-R GGTGGACTGGGAGTGGGTTTCT AGT-F TGGATGTTGCTGCTGAGAAGATTGA AGT-R CTTGGAAGTGGACGTAGGTGTTGAA TGFB2-F TGCCATCCCGCCCACTTTCT TGFB2-R GCCATTCGCCTTCTGCTCTTGT SERPINE1-F TGGTGCTGGTGAATGCCCTCT SERPINE1-R GTGCTGCCGTCTGATTTGTGGAA PIK3CD-F GACACCATCGCCAACATCCAACT PIK3CD-R CACAATAGCCAGCACAGGAGAGG COL4A1-F CCACAGGGACCACCAGGACAAA COL4A1-R TTCCAGCGAAACCAGGCAAGC AKT3-F CAGAACGACCAAAGCCAAACACATT AKT3-R AGTCTGTCTGCTACAGCCTGGATAG SLC27A5-F GCAGCATGGCGTGACAGTGAT SLC27A5-R GTTGCCTTCTGTGGAGCCGTAG ERG1-F CACGAACGCCCTTACGCT ERG1-R CATCGCTCCTGGCAAACT CXCL8-F CCACCGGAGCACTCCATAAG CXCL8-R GATGGTTCCTTCCGGTGGTT CCL2-F TCTGTGCCTGCTGCTCATAG CCL2-R GGGCATTGATTGCATCTGGC IL1A-F AAGACAGTTCCTCCATTGAT IL1A-R GATACTCAGAGACACAGATTG FOSB-F CTTGTGCAACCCACCCTCA FOSB-R GCCACTGCTGTAGCCACTCAT MMP1-F GCTCATGAACTCGGCCATTCTCTTGGACT MMP1-R CGGGTAGAAGGGATTTGTGCGCATGTA PCK1-F CGGAAAGAAACCTGTGGATCTC PCK1-R CAGATGTGGATGTGATCAGGCT NOS3-F GTGATGGCGAAGCGAGTGAAGG NOS3-R TTACCACCAGCACCAGCGTCTC Β-actin-F CCTGACTGACTACCTCATGAAG β-actin-R GACGTAGCACAGCTTCTCCTTA Table 2. The mass spectral information of CC-MGO adducts, CGAs and CHAs Adducts Adduct name Molecular formula Peak time (min) Molecular weight ( m/z ) Parent ion ( m/z ) Inaccuracies (ppm) Ion fragment ( m/z ) CC-MGO adducts Mono CC-mono MGO adduct C 18 H 18 O 8 4.14 361.09289 361.09268 0.58 343.08206，289.07174，181.04971 Mono CC-di MGO adduct C 21 H 22 O 10 4.06 433.11402 433.11337 1.50 415.10324，361.09268，343.08206，263.05576 Di CC-mono MGO adduct C 33 H 32 O 14 4.15 651.17193 651.17188 0.08 361.09268，343.08206，289.07174，245.08145，181.04970 Di CC-di MGO adduct C 36 H 36 O 16 4.15 723.19306 723.19299 0.10 361.09268，289.07174，245.08145，181.04970 CGAs Mono CC-mono GO adduct C 17 H 16 O 8 3.54 347.07724 347.07675 1.41 289.07174，245.08145，205.04953，167.03365，123.04401，109.02809 Di CC-mono GO adduct C 32 H 30 O 14 3.64 637.15628 637.15588 0.63 347.07675，289.07174，245.08145，205.04953，167.03365，123.04401，109.02809 Di CC-di GO adduct C 34 H 32 O 16 3.65 695.16176 695.16144 0.46 289.07174，245.08145，167.03365，109.02809 CHAs Mono CC-mono 5-HMF adduct C 21 H 20 O 9 4.6 415.10346 415.10306 0.96 289.07174，245.08145，205.04953，167.03365，123.04401，109.02809 Mono CC-di 5-HMF adduct C 21 H 20 O 9 4.35 541.13515 541.13495 0.37 289.07174，245.08145，123.04401 Table 3. Annotation table of GO function of differential genes between CK group and AGEs group (TOP 10) Go second level annotation Types Name Gene count GO0009987 Biological process Cellularprocess 324 GO0005488 Molecular function Binding 308 GO0044699 Biological process Single-organismprocess 262 GO0008152 Biological process Metabolicprocess 228 GO0065007 Biological process Biologicalregulation 228 GO0050789 Biological process Regulationofbiologicalprocess 210 G:0003824 Molecular function Catalyticactivity 206 GO0050896 Biological process Responsetostimulus 139 GO0005623 Cellular composition Cell 134 GO0044464 Cellular composition Cellpart 134 Table 4. Annotated Table of Differential Gene GO Functions between AGEs Group and CMAs Group (TOP 10) Go second level annotation Types Name Gene count GO0005488 Molecular function Binding 23 GO0009987 Biological process Cellular process 17 GO0008152 Biological process Metabolic process 15 GO0044699 Biological process Single-organism process 12 GO0003824 Molecular function Catalytic activity 10 GO0005623 Cellular composition Cell 8 GO0044464 Cellular composition Cell part 8 GO0043226 Cellular composition Organelle 7 GO0050789 Biological process Regulation of biological process 7 GO0065007 Biological process Biological regulation 7 Table 5. Differentially expressed gene KEGG between CK group and AGEs group Pathway ID Pathway description Gene count map04668 TNF signaling pathway 19 map04064 NF-κB signaling pathway 15 map00010 Glycolysis / Gluconeogenesis 11 map02010 ABC transporters 8 map04010 MAPK signaling pathway 27 map04657 IL-17 signaling pathway 12 map04151 PI3K-Akt signaling pathway 31 map04630 JAK-STAT signaling pathway 17 map04933 AGE-RAGE signaling pathway in diabetic complications 12 map04350 TGF-beta signaling pathway 11 Table 6. Differentially expressed gene KEGG between AGEs group and CMAs group Pathway ID Pathway description Gene count map03320 PPAR signaling pathway 3 map05020 Prion disease 2 map00010 Glycolysis / Gluconeogenesis 2 map04657 IL-17 signaling pathway 2 map04974 Protein digestion and absorption 2 map04931 Insulin resistance 2 map00120 Bile acid metabolism 1 map04371 Apelin signaling pathway 2 map04964 Proximal tubule bicarbonate reclamation 1 map00020 Citrate cycle (TCA cycle) 1 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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12:29:15","extension":"html","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":214784,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8521410/v1/40ef2a80851d50e99d526d73.html"},{"id":100371984,"identity":"54a6e8db-4c08-4899-97a6-8d60330fb483","added_by":"auto","created_at":"2026-01-16 08:11:19","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":496444,"visible":true,"origin":"","legend":"\u003cp\u003eTrapping capacity of three carbonyl compounds, MGO, GO, and 5-HMF by CC.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8521410/v1/0cdb9a41e7c1c4eb24cccac0.png"},{"id":100235703,"identity":"52c318dc-4c4c-47b1-86bc-8b9d849939b0","added_by":"auto","created_at":"2026-01-14 12:29:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3226813,"visible":true,"origin":"","legend":"\u003cp\u003eThe total ion chromatography for CC-MGO adducts (A), Secondary mass spectra (B, C, D, E), The structures of the corresponding adducts (F, G, H, I).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8521410/v1/f020a2d8ac0238d71439630e.png"},{"id":100235704,"identity":"6659e441-61da-4e38-a220-de344dead376","added_by":"auto","created_at":"2026-01-14 12:29:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2757316,"visible":true,"origin":"","legend":"\u003cp\u003eThe total ion chromatography for CGAs (A), Secondary mass spectra (B, C, D), The structures of the corresponding adducts (E, F, G).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8521410/v1/fa60cb5ae1c9decdc1308493.png"},{"id":100370805,"identity":"b4028ab7-7131-4840-bf82-822a40eb5c9a","added_by":"auto","created_at":"2026-01-16 08:08:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2454213,"visible":true,"origin":"","legend":"\u003cp\u003eThe total ion chromatography for CHAs (A), Secondary mass spectra (B, C), The structures of the corresponding adducts (D, E).\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8521410/v1/4546958b9ebbadb8f2a54835.png"},{"id":100371034,"identity":"d36d8725-edfd-4b13-ba2f-295a241abf40","added_by":"auto","created_at":"2026-01-16 08:09:13","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2324843,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of the two separation methods (A), HSCCC of CC-MGO adducts (B), The semi-preparative liquid chromatogram of CC-MGO adducts (C).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8521410/v1/33836d4ba8ecdc85c8e771a1.png"},{"id":100370866,"identity":"a7b1fe09-c782-4b4e-8aba-0c1f67e5fe30","added_by":"auto","created_at":"2026-01-16 08:08:48","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":5572830,"visible":true,"origin":"","legend":"\u003cp\u003eThe heating simulation systemlactose/L-lysine simulation system and milk system were chosen to explore the inhibitory effect of CC-MGO adducts on the generation of AGEs in the system (A), Scavenging effect of CC-MGO adducts on ABTS\u003csup\u003e+\u003c/sup\u003e radicals and DPPH radicals (B), Effect of lysine concentration on the inhibition of AGEs by CC-MGO adducts (C), Color before and after heating in lactose/L-lysine simulation system with the addition of different concentrations of CC-MGO adducts (D), Inhibitory effect of CC-MGO adducts concentration on AGEs in lactose/L-lysine simulation system (E), Color before and after heating in milk with the addition of different concentrations of CC-MGO adducts (F), Inhibitory effect of CC-MGO adducts concentration on AGEs in milk (G), Inhibitory effect of AG concentration on AGEs in lactose/L-lysine simulation system (H), Color before and after heating in lactose/L-lysine simulation and milk systems with the addition of different concentrations of AG (I), Inhibitory effect of AG concentration on AGEs in milk (J). Values are mean ± SD. Means with different letters are significantly different (p \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8521410/v1/b202350559f33350dc1f59ce.png"},{"id":100371547,"identity":"6f34d6aa-fbbe-4f1c-9b69-653de4d65413","added_by":"auto","created_at":"2026-01-16 08:10:30","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1410686,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of CC-MGO adducts and MGO on cell viability of Caco-2 cells (A), The changes of free amino group contents during glycation at 100℃ and fluorescence spectra of BSA, heated BSA and AGEs (B), Effect of AGEs on cell viability of Caco-2 cells (C), Effect of CC-MGO adducts on the cellular activity of AGEs (D). Values are mean ± SD. Means with different letters are significantly different (p \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8521410/v1/6f6050b27e8db13fb735a4ee.png"},{"id":100235711,"identity":"9bad752c-7200-4b0b-b185-48c8ec564f94","added_by":"auto","created_at":"2026-01-14 12:29:14","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":3706958,"visible":true,"origin":"","legend":"\u003cp\u003ePlot of principal component analysis results (A), Volcano plot of differentially expressed genes between control check (CK) group and AGEs group (B), Volcano plot of differentially expressed genes between AGEs group and CC-MGO adducts group (C), Differential gene GO function annotation between CK group and AGEs group (D), Differential gene GO function annotation between AGEs group VS CC-MGO adducts group (E), Bubble map of KEGG enrichment of differential genes between CK group and AGEs group (F), Bubble map of KEGG enrichment of differential genes between AGEs group and CC-MGO adducts group (G). Group CK: control; Group AGEs: group after treatment with AGEs; Group CMAs: group treated with AGEs after CC-MGO adducts preincubation.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8521410/v1/c99feb42723b88ff9ee5d076.png"},{"id":100371293,"identity":"1bd9f80a-b2ec-4670-8071-a99e8e6d5bff","added_by":"auto","created_at":"2026-01-16 08:09:46","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":3788302,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart of PCR experiment (A), Gene expression on signaling pathways (B), Effect of CK group and AGEs group on AGE-RAGE signaling pathway (C), Effect of AGEs group and CC-MGO adducts group on PPAR and IL-17 signaling pathway (D). Values are mean ± SD. Means with different letters are significantly different (p \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-8521410/v1/0d9cef6d8a5257af872fd277.png"},{"id":103738792,"identity":"8fd16479-b562-4152-aff4-773f122d922c","added_by":"auto","created_at":"2026-03-02 10:27:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":27471808,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8521410/v1/a7e3fe38-4708-4bd8-a508-70007c603377.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A novel perspective on the amelioriating effects of catechin-carbonyl adducts on AGEs toxicity","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe formation of advanced glycation end products (AGEs) occurs through the Maillard reaction (MR), a non-enzymatic condensation process involving the interaction between the carbonyl group of a reducing sugar and the free amine of a nucleic acid, protein, or lipid. AGEs have the ability to interact with the receptor of advanced glycation end products (RAGE), there by modulating a wide range of cell signalling pathways. The accumulation of AGEs in the body can lead to a wide range of health effects, including the development of diabetes\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, cardiovascular disease\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, neurological disorders\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, and cancer\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Indeed, preventing the formation or accumulation of AGEs holds promise as an effective strategy for managing and controlling chronic health diseases associated with AGEs.\u003c/p\u003e \u003cp\u003eReactive carbonyl compounds (RCS), including methylglyoxal (MGO), glyoxal (GO), and 5-hydroxymethylfurfural (5-HMF), are abundantly produced during the intermediate stages of the Maillard reaction (MR)\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. These compounds form covalent bonds with nucleophilic sites in DNA, RNA, proteins, and phospholipids through Michael addition and the Schiff base reaction. MGO, GO, and 5-HMF can react with amino acids, leading to the formation of AGEs like carboxymethyl lysine (CML), carboxyethyl lysine (CEL), and 3-deoxyglucose ketone (3-DG)\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, which may be harmful to the body\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Considering that carbonyl compounds are precursors of typical AGEs, the scavenging mechanism of carbonyl compounds has become a popular and important area of research.\u003c/p\u003e \u003cp\u003eNatural polyphenols, widely found in various sources, are known for their antioxidant, anti-inflammatory, and anti-tumor properties\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. According to Zhang et al., there are four main mechanisms by which polyphenols inhibit the MR: scavenging of free radicals, inactivation of transition metals, formation of protein-phenolic complexes, and the capacity to trap carbonyl compounds\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Catechin (CC), a polyphenol constituent of daily diets, is ubiquitously distributed across diverse food systems as a key bioactive compound in plant-based nutrition. As a principal dietary polyphenol, its primary sources include green tea leaves, apple peels, berry species, and cocoa beans. As a plant polyphenols, CC potent bioactivity in scavenging free radicals and modulating nuclear NF-κB signaling pathways, thereby effectively attenuating oxidative stress and suppressing pro-inflammatory cytokine production. Chen et al. demonstrated that CC with hydroxyl groups at the C-6 and C-8 positions of the A-ring could effectively bind to MGO or GO adducts in the system, which inhibited MGO or GO-mediated protein glycosylation, thereby impeding the formation of AGEs\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn addition, in food processing, especially foods with baking as the main process, such as bread and biscuits, contain a large amount of AGEs. However, the generation of polyphenols-carbonyl compounds by capturing the carbonyl intermediate MG/MGO by polyphenols can effectively reduce the AGEs generated in food processing\u003csup\u003e\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. While flavonoids such as hesperidin and resveratrol can inhibit the production of AGEs by lowering plasma MG concentrations, which is thought to help overweight and obese subjects increase their metabolism and vascular health, further illustrating that different types of polyphenols may promote health through the effects of different factors on AGEs\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, there are no studies demonstrating whether the adducts formed by CC-captured carbonyl compounds are detrimental to cells / the body, or if they possess beneficial activities that could further inhibit the production of AGEs or mitigate AGE-induced damage. Quercetin-containing foods can scavenge reactive aldehydes, but at the same time highly-purified adducts (Que-mono-MGO and Que-di-MGO) were found to display higher cytotoxicity than their precursor MGO and quercetin\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. On the other hand, the studie has discovered that apigenin and phloretin effectively interacted with MGO within human umbilical vein endothelial cells (HUVECs), the resulting polyphenol-carbonyl adducts significantly reduced reactive oxygen species (ROS) production and protein expression by 30\u0026ndash;70%, producing a significant inhibitory effect on oxidative stress and inflammation in cells\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Phloretin-MGO adducts were also shown to inhibit AGE-induced inflammation in endothelial cells\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Chen et al. reported that although rutin-MGO adducts mildly inhibited cell proliferation at high concentrations, their toxicity was much lower than that of MGO\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Furthermore, EGCG\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, dietary genistein\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, and myricetin\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e were also effective in trapping MGO to form adducts, thereby reducing AGEs production.\u003c/p\u003e \u003cp\u003eIt appears that different polyphenol-carbonyl adducts generally have different properties. However, the limited number of studies mentioned above also failed to reach consistent conclusions regarding the nature of adducts, particularly in various systems such as food systems and cellular animal models. Therefore, there is a need for continued in-depth studies on the bioactivity of CC-carbonyl adducts and their effect on the MR.\u003c/p\u003e \u003cp\u003eAt present, the production of AGEs is greatly promoted by the high-fat and high-protein animal-derived nature during thermal processing, and even increases the content of AGEs by 10\u0026ndash;100 times compared to unheated food. Therefore, the heating simulation system of lactose and L-lysine was selected to explore the inhibitory effect of CC-MGO adduct on AGEs. Subsequently, AGEs were prepared and cell models were established to investigate the amelioration of AGEs-induced cytotoxicity by CC-MGO adducts. In the study, the CC-MGO adducts were first prepared and separated using high-speed counter-current chromatography (HSCCC) and semi-preparative liquid chromatography. Transcriptomics and reverse transcription polymerase chain reaction (RT-PCR) were employed to further elucidate the regulatory effects of CC-MGO adducts on signaling pathways. In summary, this study not only demonstrated the potential of CC-MGO adducts in resisting AGEs-induced cytotoxicity but also elucidated their possible molecular mechanisms of action. These findings provide a crucial scientific foundation for utilizing natural compounds in the prevention and treatment of AGEs-related diseases.\u003c/p\u003e"},{"header":"Result and discussion","content":"\u003cp\u003e\u003cstrong\u003eTrapping capacity of three carbonyl compounds by CC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs depicted in Figure 1, CC exhibited significant scavenging ability for MGO, GO, and 5-HMF. The trapping capacities of these three carbonyl compounds by CC were as follows: MGO (94.81 \u0026plusmn; 2.68%), GO (43.09 \u0026plusmn; 3.51%), and 5-HMF (25.34 \u0026plusmn; 3.07%), respectively. CC showed the highest clearance of MGO, followed by GO and the lowest by 5-HMF, which was consistent with the study of Chen et al\u003csup\u003e13\u003c/sup\u003e. MGO reacted with the hydroxyl group of CC through addition or condensation reactions, resulting in a higher capture rate due to its greater efficiency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStructural identification of CC with MGO, GO, 5-HMF\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe corresponding mass spectral information identified for these three adducts under the conditions specified are shown in Table 2. As depicted in Figure 2A, CC-MGO adducts and CC mostly appeared within the 3-5 min range and were difficult to separate, while MGO itself appeared around 5-6 min. After conducting mass spectrometry analysis, four potential combined products of CC-MGO adducts with mass-to-charge ratios \u003cem\u003em/z\u003c/em\u003e of 361.09, 433.11, 651.16, and 723.18 were identified, which is consistent with the findings of Han et al\u003csup\u003e25\u003c/sup\u003e. The secondary mass spectra and potential structures of the identified reaction products are presented in Figure 2.\u003c/p\u003e\n\u003cp\u003eThe first adduct exhibited an ion at \u003cem\u003em/z\u003c/em\u003e 361.09 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e), corresponding to one CC molecule (\u003cem\u003em/z\u003c/em\u003e 289.07) combined with one MGO molecule (\u003cem\u003em/z\u003c/em\u003e 71.01). The fragment ions at \u003cem\u003em/z\u003c/em\u003e 343.08, 289.07, and 181.05 were identified as components of a mono CC-mono MGO adduct. The fragment at \u003cem\u003em/z\u003c/em\u003e 343.08 ([M\u0026minus;H\u0026minus;H\u003csub\u003e2\u003c/sub\u003eO]\u003csup\u003e\u0026minus;\u003c/sup\u003e) resulted from the loss of a water molecule (H\u003csub\u003e2\u003c/sub\u003eO) from \u003cem\u003em/z\u003c/em\u003e 361.09 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e), while the fragment at \u003cem\u003em/z\u003c/em\u003e 289.07 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e) originated from CC. Additionally, the fragment at \u003cem\u003em/z\u003c/em\u003e 181.05 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e) was derived from the fragmentation of \u003cem\u003em/z\u003c/em\u003e 343.08 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e). According to Sang et al\u003csup\u003e23\u003c/sup\u003e, CC primarily traps active carbonyl compounds via the A-ring at the C6 or C8 position. However, mass spectrometry did not allow for differentiation between these isomers. As a result, the structural formula of one isomer is presented in Figure 2F. The second adduct exhibited an ion at \u003cem\u003em/z\u003c/em\u003e 433.11 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e), consisting of one CC molecule (\u003cem\u003em/z\u003c/em\u003e 289.07) and two MGO molecules (\u003cem\u003em/z\u003c/em\u003e 71.01). The fragment ions at \u003cem\u003em/z\u003c/em\u003e 415.10, 361.09, 343.08, and 263.06 were identified as components of a mono CC-di MGO adduct (Figure 2G). The fragment at \u003cem\u003em/z\u003c/em\u003e 415.10 ([M\u0026minus;H\u0026minus;H\u003csub\u003e2\u003c/sub\u003eO]\u003csup\u003e\u0026minus;\u003c/sup\u003e) was produced by the loss of a water molecule from \u003cem\u003em/z\u003c/em\u003e 433.11 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e). At this stage, MGO was attached to both the C6 and C8 positions of CC through electrophilic substitution. Previous studies have reported that CC can undergo cross-linking reactions with MGO. The third adduct exhibited an ion at \u003cem\u003em/z\u003c/em\u003e 651.16 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e), composed of two CC molecules (\u003cem\u003em/z\u003c/em\u003e 289.07) and one MGO molecule (\u003cem\u003em/z\u003c/em\u003e 71.01). Fragment ions at \u003cem\u003em/z\u003c/em\u003e 361.09, 343.08, 289.07, 245.08, and 181.05 were identified as a di CC-mono MGO adduct (Figure 2H). The fragment at \u003cem\u003em/z\u003c/em\u003e 245.08 ([M\u0026minus;H\u0026minus;CH\u003csub\u003e2\u003c/sub\u003e-CHOH]\u003csup\u003e\u0026minus;\u003c/sup\u003e) resulted from the loss of a -CH\u003csub\u003e2\u003c/sub\u003e-CHOH group from \u003cem\u003em/z\u003c/em\u003e 289.07 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e). The fourth adduct exhibited an ion at \u003cem\u003em/z\u003c/em\u003e 723.18 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e), consisting of two CC molecules (\u003cem\u003em/z\u003c/em\u003e 289.07) and two MGO molecules (\u003cem\u003em/z\u003c/em\u003e 71.01). The fragment ions at \u003cem\u003em/z\u003c/em\u003e 361.09, 289.07, 245.08, and 181.05 were identified as a di CC-di MGO adduct (Figure 2I). In this adduct, the carbonyl groups of MGO reacted with both CC molecules via electrophilic substitution\u003csup\u003e26\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe adducts of EGCG (epigallocatechin gallate), the major catechin in tea, with MGO have been structurally characterized and identified as 8-MGO-substituted EGCG, 6-MGO-substituted EGCG, or 6,8-di-MGO-substituted EGCG\u003csup\u003e27\u003c/sup\u003e. Based on this, and supported by our structural analysis of the products formed from the reaction between CC and MGO, it can be hypothesized that the formation of these adducts is primarily driven by electrophilic substitution of the MGO carbonyl group onto the aromatic ring of the catechin molecules. Since both GO and 5-HMF contain a carbonyl group, it is plausible to assume that the reaction of CC with GO and HMF may occur in a similar manner as with MGO.\u003c/p\u003e\n\u003cp\u003eThe structures of CC\u0026amp;GO adducts (CGAs) were shown in Figure 3, CGAs mostly appeared within the 3-5 min range, while GO itself appeared around 4-5 min. Mass spectrometry analysis inferred that there were three potential addition and reaction products of CC with GO.\u003c/p\u003e\n\u003cp\u003eThe first adduct exhibited an ion at \u003cem\u003em/z\u003c/em\u003e 347.08 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e), corresponding to one CC molecule (\u003cem\u003em/z\u003c/em\u003e 289.07) combined with a GO molecule (\u003cem\u003em/z\u003c/em\u003e 57.00). The fragment ions at \u003cem\u003em/z\u003c/em\u003e 289.07, 245.08, 205.50, 167.03, 123.04, and 109.03 were identified as part of a mono CC-mono GO adduct. The fragments at \u003cem\u003em/z\u003c/em\u003e 245.08 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e), 205.50 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e) and 167.03 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e) were from CC as previously reported. The fragments at \u003cem\u003em/z\u003c/em\u003e 123.04 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e), and 109.03 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e) were from the fragments at \u003cem\u003em/z\u003c/em\u003e 347.08 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e). The second adduct displayed an ion at \u003cem\u003em/z\u003c/em\u003e 637.15 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e), which was two CC (\u003cem\u003em/z\u003c/em\u003e 289.07) with a GO (\u003cem\u003em/z\u003c/em\u003e 57.00), and the fragment ions with \u003cem\u003em/z\u003c/em\u003e 347.08, 289.07, 245.08, 205.50, 167.03, 123.04 and 109.03 were identified as a di CC-mono GO adduct (Figure 3F). The third adduct displayed an ion at \u003cem\u003em/z\u003c/em\u003e 637.15 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e), which was two CC (\u003cem\u003em/z\u003c/em\u003e 289.07) with two GO (\u003cem\u003em/z\u003c/em\u003e 57.00), and the fragment ions with \u003cem\u003em/z\u003c/em\u003e 289.07, 245.08, 167.03 and 109.03 were identified as a di CC-di MGO adduct (Figure 3G).\u003c/p\u003e\n\u003cp\u003eThe structures of CC and 5-HMF adducts (CHAs) were shown in Figure 4, CHAs mostly appeared within the 4-5 min range, while 5-HMF itself appeared around 2 min. Mass spectrometry analysis inferred that there were two potential addition and reaction products of CC with 5-HMF. The first adduct displayed an ion at \u003cem\u003em/z\u003c/em\u003e 415.10 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e), was identified as a mono CC-mono 5-HMF adduct. The second adduct displayed an ion at \u003cem\u003em/z\u003c/em\u003e 541.13 ([M\u0026minus;H]\u003csup\u003e\u0026minus;\u003c/sup\u003e), was identified as a mono CC-di 5-HMF adduct.\u003c/p\u003e\n\u003cp\u003eSince CC-MGO adducts were the most straightforward to separate compared to CGAs and CHAs, MGO was selected as a representative carbonyl compound for the subsequent experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstablishment of a method for the preparation of CC-MGO adducts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA mixture of CC-MGO adducts was obtained through HSCCC and semi-preparative liquid chromatography for separation and purification (Figure 5A). In Figure 5B, the chromatogram illustrated the semi-preparative liquid phase separation of CC-MGO adducts. The samples with four peaks in the figure were collected individually and analyzed using LC-MS/MS. It was separated that the sample was isolated at 30-35 minutes. Figure 5C presented the analysis of three sets of samples separated by HSCCC. As illustrated in Figure 5B and 5C, HSCCC proved to be more effective than semi-preparative liquid chromatography for the separation of CC-MGO adducts. Therefore, HSCCC was selected for the subsequent experiments to separate CC-MGO adducts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntioxidant properties of CC-MGO adducts and the inhibitory effects on AGEs\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eformation\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ein simulation and milk food system\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo prepare CC-MGO adducts for further studies in simulated and real food systems (Figure 6A), it is essential to first ascertain their beneficial antioxidant properties. Indeed, both the DPPH and the ABTS+ method were valuable tools for evaluating the antioxidant potential of compounds. As presented in Figure 6B, CC-MGO adducts exhibited significant scavenging effects on both DPPH radicals and ABTS+ radicals, with the dose-dependent scavenging effects. The radical scavenging activity of phenolics primarily relied on factors such as the dissociation energy of the hydroxyl group binding, the resonance dissociation stability of the phenoxyl radical, and the site-blocking effect caused by substituents present in the aromatic ring. These characteristics significantly influenced phenolic compounds\u0026apos; antioxidant capacity\u003csup\u003e28\u003c/sup\u003e. The phenolic hydroxyl and polyhydroxyl configurations of CC have been reported as the active sites responsible for scavenging free radicals in antioxidant activity\u003csup\u003e29\u003c/sup\u003e. Although the formation of CC-MGO adducts alters the structure of CC, primarily affecting the A-ring as shown in Figure 2A, the key phenolic hydroxyl groups, particularly the catechol structure on the B-ring, which serves as the main site for CC\u0026rsquo;s potent radical-scavenging activity through hydrogen donation and radical stabilization\u003csup\u003e30,31\u003c/sup\u003e, remain intact. Therefore, the ABTS⁺ and DPPH scavenging activities observed in CC-MGO adducts are mainly attributed to the preservation and availability of these critical phenolic hydroxyl groups, with their intrinsic antioxidant capacity largely unaffected by modifications to the A-ring. Since CC-MGO adducts retained the four phenolic hydroxyl groups present in the structure of CC, it was assumed that CC-MGO adducts also maintained the antioxidant capacity of CC.\u003c/p\u003e\n\u003cp\u003eHeated lactose/L-lysine simulation system and milk system were chosen to explore the inhibitory effect of CC-MGO adducts on the generation of AGEs in simulated food system. In the lactose/lysine system, MR occurred between the carbonyl group of lactose and the amino group of L-lysine. When the concentration of L-lysine was 30 mM, the CMAs began to show an inhibitory effect on the generation of AGEs in the simulated system, which may be due to the fact that the reaction of L-lysine with lactose was basically reacted completely. As depicted in Figure 6C, it was observed that CC-MGO adducts exhibited a promoting effect on the generation of AGEs in simulated food system at a concentration of L-lysine of 60 mM. Based on the structural properties of the adduct, which retained the carbonyl group of MGO, it was assumed that after the reaction of L-lysine with lactose, L-lysine could still continue to occur MR with the carbonyl group on the CC-MGO adducts, thus promoting the generation of AGEs. At an L-lysine concentration of 30 mM, CC-MGO adducts exhibited an inhibitory effect on the generation of AGEs in simulated food system, which was likely because the reaction between L-lysine and lactose had reached a state of near completion. In contrast, the MGO during the MR is much larger than the binding site of CC-MGO adducts, so the overall inhibition rate is only 20%. The inhibition of AGEs in simulated food system by CC-MGO adducts reached 50% at L-lysine concentrations of 12, 15 and 20 mM. The mechanism of inhibition of AGEs by CC-MGO adducts was hypothesized to be two pathways: (1) Carbonyl compounds were generated by oxidative reactions during the maillard reaction, e.g., direct oxidative degradation of glucose, and oxidative degradation of Schiff base during the MR\u003csup\u003e32\u003c/sup\u003e. The antioxidant results show that CC-MGO adducts had good free radical scavenging ability and can inhibit the formation of carbonyl compounds and AGEs during the MR by antioxidant mechanism. (2) MGO induced the formation of AGEs from amino acids or free amino acid residues in proteins, and there were still binding sites in CC-MGO adducts that were not fully reacted with MGO, so the formation of AGEs can be inhibited by capturing MGO. Our LC-MS analysis confirmed the formation of multiple CC-MGO adducts in the isolated samples, including mono-CC-mono-MGO, mono-CC-di-MGO, di-CC-mono-MGO, and di-CC-di-MGO species. Notably, the detection of mono-MGO-bound adducts (e.g., mono-CC-mono-MGO and di-CC-mono-MGO) suggests the presence of unreacted nucleophilic sites, such as the C6 and C8 positions on the catechin A-ring or free phenolic hydroxyl groups, within these adducts. This structural feature is consistent with previous findings by Liu et al\u003csup\u003e33\u003c/sup\u003e,\u0026nbsp;who demonstrated that di-MGO-quercetin adducts retained the capacity to bind additional MGO molecules, forming tris-MGO-quercetin complexes. Based on this analogy, we propose that CC-MGO adducts, particularly those containing only one MGO moiety, may retain residual MGO-scavenging capacity through their unoccupied reactive sites. This ability to further sequester free MGO may underlie the observed suppression of AGEs formation, thereby enhancing the functional role of these adducts in mitigating glycation-related cellular damage. Since there was no significant difference between the L-lysine concentration of 20 mM and 12 mM, an L-lysine concentration of 20 mM was selected for the experiment.\u003c/p\u003e\n\u003cp\u003eIn order to imitate the MR triggered by milk pasteurization at 65\u0026deg;C for 30 minutes, an authentic milk system was established. To assess the capacity of CC-MGO adducts to impede the formation of AGEs in both contexts, varying concentrations of CC-MGO adducts were added to the lactose/L-lysine simulation system and the milk system, respectively. Figure 6D and 6F visually illustrated that the sample solution assumed a progressively more intense yellow tint as the concentration of CC-MGO adducts added prior to heating increased. This color shift could likely be attributed to the inherent yellow pigmentation of CC-MGO adducts themselves. The sample solution in the simulated system eventually turned brown as it heated up because the late stages of the MR would produce brown macromolecules, such as melanoidins compounds, which would change the color of the solution. Meanwhile, this system simulates real food processing by applying heat, which promotes the Maillard reaction between the carbonyl group of lactose and the amino group of L-lysine, resulting in increased formation of AGEs. In contrast, within the milk system, due to the irregular reflection of light caused by fat globules and protein particles, the color of the solution remained unaltered both before and after the heating procedure.\u003c/p\u003e\n\u003cp\u003eThe formation mechanism of AGEs was complex, and cross-linking between amino acids could produce representative AGEs such as pentosidine, argpyrimidine, crossline and vesperlysine, which were all autofluorescent. Measuring the fluorescence value could be a simple and effective way to measure the content of fluorescent AGEs, and the magnitude of the fluorescence value could measure the amount of fluorescent AGEs generated, so as to calculate the inhibition rate of CC-MGO adducts on AGEs. As illustrated in Figure 6E and 6G, it was evident that the inhibitions of AGEs, pentosidine, argpyrimidine, crossline, and vesperlysine were higher with increasing concentrations of CC-MGO adducts. The results obtained from this experiment were in agreement with the findings reported by Liu et al\u003csup\u003e33\u003c/sup\u003e. Notably, comparison with the positive control AG (Figure 6E, 6G, 6H, 6I, 6J) showed that 1 mM CC-MGO achieved a similar inhibition rate to 5 mM AG, confirming their strong potential to suppress AGEs formation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInhibition of AGEs cytotoxicity by CC-MGO adducts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe cell viability of MGO and CC-MGO adducts was assessed using the CCK8 assay to screen for appropriate concentrations. As depicted in Figure 7A, in the Caco-2 cell model, cell viability decreased with increasing concentrations of CC-MGO adducts and MGO. At a concentration of 50 \u0026mu;M, no significant difference in cytotoxicity was observed between the CC-MGO adducts and MGO, with cell viability remaining above 95%. However, as the concentration increased, notable differences emerged. At 2000 \u0026mu;M, the viability of Caco-2 cells in the MGO group was 78.76 \u0026plusmn; 0.53%, whereas in the CC-MGO adduct group, it was significantly higher at 84.90 \u0026plusmn; 2.42%. Used the concentration of the CC-MGO adducts at which Caco-2 cell viability was not lower than 80% for subsequent experiments,which was determined to be lower than 2000 \u0026mu;M.\u003c/p\u003e\n\u003cp\u003eFigure 7B presents the alterations in free amino acids observed during the glycation process of bovine serum albumin. The free amino acid content of bovine serum albumin heated alone was notably high at 97.10 \u0026plusmn; 4.26%, whereas the free amino acid content of the model AGEs formed after heating with MGO drastically reduced to 20.51 \u0026plusmn; 0.08%. This substantial decrease in the relative content of amino groups in the AGEs model, compared to bovine serum albumin heated alone, suggests effective binding of the carbonyl group on MGO with the amino group on bovine serum albumin. Consequently, the successful construction of the glycation model is inferred. And the fluorescence intensity of AGEs exhibited a more pronounced decrease compared to that of natural bovine serum albumin. This phenomenon can be attributed to the close linkage or interaction between the carbonyl group in MGO and the amino acid residues in bovine serum albumin, resulting in a certain shielding effect that diminishes the overall fluorescence. Concurrently, the redshift observed in the emission wavelength of AGEs indicates an increase in the polarity of the surroundings of the amino acid residues. This shift suggests that the hydrophobic amino acids within the AGEs molecule are more exposed to the surface compared to natural bovine serum albumin, leading to a redshift in peak emission following the MR\u003csup\u003e34\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe cell viability of AGEs was assessed using the CCK8 method. As illustrated in Figure 7C, low concentrations of AGEs, such as 5 mg/mL, exhibited a minor effect on Caco-2 cell viability, yielding a viability of 85.51 \u0026plusmn; 1.86%. However, with increasing concentrations of AGEs, a significant decrease in cell viability was observed, indicating a gradual increase in toxicity. At a concentration of 30 mg/mL, cell viability dropped close to 50%. Subsequently, at concentrations of 35 and 40 mg/mL, cell viability decreased markedly to approximately 30%, signifying intensified toxicity. Following literature guidance\u003csup\u003e35\u003c/sup\u003e, the AGEs concentration corresponding to 50% cell viability of Caco-2 cells was chosen for subsequent CCK8 toxicity experiments, which was determined to be 30 mg/mL.\u003c/p\u003e\n\u003cp\u003eThe inhibitory effect of CC-MGO adducts on the cytotoxicity induced by AGEs was assessed using the CCK8 assay. Based on the experimental results outlined above, a concentration of 30 mg/mL of AGEs was selected for this investigation. Comparative analysis with the cell viability of the control group revealed that CC-MGO adducts demonstrated an inhibitory effect on AGEs-induced cytotoxicity when its concentration was equal to or less than 500 \u0026mu;M. However, when the concentration of CC-MGO adducts exceeded 750 \u0026mu;M, both CC-MGO adducts and AGEs exhibited toxicity towards Caco-2 cells, thereby affecting cell viability. As depicted in Figure 7D, it is evident that CC-MGO adducts at a concentration of 100 \u0026mu;M exerted the most significant inhibitory effect on AGEs-induced cytotoxicity, resulting in a notable increase in cell viability to 135.19 \u0026plusmn; 1.79% compared to the cellular control group adding AGEs. Conversely, with an increase in CC-MGO adducts concentration, there was a gradual decline in Caco-2 cell viability in the presence of both CC-MGO adducts and AGEs. Particularly noteworthy is the observation that at a CC-MGO adducts concentration of 2000 \u0026mu;M, Caco-2 cell viability plummeted to only 45.65 \u0026plusmn; 2.56% of that observed in the control group. Based on the findings of this experiment, subsequent transcriptome analysis was conducted using AGEs at a concentration of 30 mg/mL and CC-MGO adducts at a concentration of 100 \u0026mu;M. These datas clearly elucidate the inhibitory effect of CC-MGO adducts on AGEs induced cytotoxicity, and provide a theoretical basis for the subsequent inhibitory mechanism of CC-MGO adducts on AGEs induced Caco-2 cytotoxicity at the transcriptional level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMechanistic analysis of the mitigating effects of CC-MGO adducts on AGE-induced cytotoxicity.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrincipal component analysis (PCA) was employed to determine the first principal component (PC1) and the second principal component (PC2) of gene expression differences among each sample. As depicted in Figure 8A, minimal differences and high biological reproducibility were observed among all three parallels in the CK, AGEs, and CC-MGO adducts groups. Simultaneously, the three sample groups exhibited substantial separation from each other, indicating variability across different groups.\u003c/p\u003e\n\u003cp\u003eThe analysis of differentially expressed genes were presented in Figure 8B and 8C, where volcano plots depict the comparison of gene expression between different groups, namely the control, AGEs, and CC-MGO adducts groups. In our analysis, genes meeting two criteria were identified as differentially expressed: a fold change in expression greater than or equal to 2 and a significant level of expression difference less than or equal to 0.05. Due to the substantial number of differentially expressed genes between the control and AGEs groups, the fold change threshold was adjusted to 2.0. Each point on the volcano plot represents a metabolite, with significantly upregulated, downregulated, and non-significant metabolites shown in red, blue, and gray, respectively. This adjustment resulted in 1143 up-regulated genes and 697 down-regulated genes between the control and AGEs groups. For example, the downregulation of EGR1, an early growth response protein among the downregulated genes, inhibited cell proliferation and induced apoptosis. In contrast, the upregulation of CXCL8, a CXC-type chemokine, initiated the inflammatory response. Conversely, between the AGEs and CC-MGO adducts groups, there were 56 differentially up-regulated genes and 78 down-regulated genes. SLC27A5, an upregulated gene, inhibited the proliferation of hepatocellular carcinoma cells to some extent, while PCK1, a downregulated gene, was associated with the promotion of diabetes mellitus development when its levels were elevated. Figure 8D illustrates the horizontal coordinates as GO-annotated secondary classifications, while the vertical coordinate represents the number of genes corresponding to each secondary classification. Total, up-regulated, and down-regulated expressed genes are depicted in blue, red, and green, respectively. The figure categorizes the differential genes in the CK and AGEs groups based on these three ontologies. Table 3 outlines the top 10 GO functional annotations, indicating enrichment across the biological process, molecular function, and cellular component ontologies. Among these annotations, six pertain to biological processes, two to molecular functions, and two to cellular components. The differential genes involved in biological processes primarily include cellular processes, metabolic processes, biological regulation, regulation of biological processes, stimulus response, and response to stimulus. In terms of molecular functions, differential genes mainly participate in binding and catalytic activity. Regarding cellular components, differential genes are primarily associated with cells, cell parts, and cellular processes. Furthermore, differential genes related to cellular components predominantly involve cell parts.\u003c/p\u003e\n\u003cp\u003eAs shown in Figure 8E and Table 4, the differential genes in the AGEs and CC-MGO adducts groups were similarly categorized by the above three ontologies. Among the top 10 GO functional annotations, five were enriched in the biological process ontology, three in the cellular location ontology, and two in the molecular function ontology. Among them, the differential genes involved in biological processes mainly include cellular process, metabolic process, single-organism process, regulation of biological process, biological regulation, and bioregulation. The differential genes involved in cell location mainly include cell, cell part and organelle; the differential genes involved in molecular function mainly include binding, catalytic activity and molecular function. The genes involved in molecular function mainly include binding and catalytic activity. Based on the results of variance analysis and KEGG annotation, the clusterProfiler software was employed to identify significantly enriched KEGG pathways using a threshold of p-value \u0026lt; 0.05. The KEGG enrichment analysis table was then utilized to generate an enrichment bubble map, visually depicting the results of the KEGG enrichment analysis.\u003c/p\u003e\n\u003cp\u003eAs illustrated in Figure 8F, KEGG enrichment bubble diagrams were constructed based on the top 10 pathways enriched by KEGG. The horizontal coordinate represents GeneRatio, indicating the ratio of the number of enriched differential genes to the entry against the total number of differential genes in the functional annotation results. The vertical coordinate depicts the entries on the enrichment. The size of the dots corresponds to the number of genes involved in the enrichment, while the color of the dots represents the p-value, with lower values indicating greater significance.\u003c/p\u003e\n\u003cp\u003eStudies have demonstrated that the initiation of diabetes and its complications by AGEs typically involves a signaling cascade mediated by RAGE\u003csup\u003e36\u003c/sup\u003e. Upon binding of AGEs to their receptor RAGE, RAGE transmits signals into the cell and mediates downstream cell signaling pathways. Binding of oligopeptide-AGEs to RAGE-V initiates downstream cell signaling, and four RAGE-mediated pathways have been identified: Ⅰ. Janus kinase (JAK) and signal transducers and activators of transcription (STAT) pathway\u003csup\u003e37\u003c/sup\u003e. Ⅱ. Phosphatidylinositide 3-kinases (PI3-K)-protein kinase B (AKT) pathway\u003csup\u003e38\u003c/sup\u003e. Ⅲ. Mitogen-activated protein kinases (MAPK) and extracellular regulated protein kinases (ERK) pathways\u003csup\u003e39\u003c/sup\u003e. Ⅳ. Reduced coenzyme II (nicotinamide adenine dinucleotide phosphate (NADPH)-ROS pathway\u003csup\u003e40\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAccording to Figure 8F and Table 5, various degrees of significant differences were observed in the four signaling pathways mentioned, as enriched in the KEGG signaling pathway analysis of the AGEs group compared to the control. Additionally, several RAGE-mediated inflammatory signaling pathways, such as the NF-\u0026kappa;B signaling pathway and the IL-17 signaling pathway, exhibited notable differences. Particularly noteworthy is the enrichment of the AGE-RAGE signaling pathway in the differential analysis, consistent with previous findings indicating that AGEs induce cytotoxicity in Caco-2 cells through binding to RAGE. This binding triggers downstream cellular signaling pathways, leading to the activation of inflammatory factors, nuclear transcription factors, and other molecules\u003csup\u003e11\u003c/sup\u003e. Therefore, the AGE-RAGE signaling pathway in diabetic complications emerges as a pivotal pathway requiring investigation in subsequent experiments.\u003c/p\u003e\n\u003cp\u003eFurthermore, KEGG enrichment analysis identified 12 significant differential genes in the AGE-RAGE signaling pathway. Among these, 7 genes were significantly up-regulated, namely CXCL8, CCL2, SERPINE1, IL1A, PIK3CD, NOS3, and AKT3, while 5 genes were significantly down-regulated, namely EDN1, EGR1, AGT, TGFB2, and COL4A1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAccording to Figure 8G and Table 6, the signaling pathways enriched by KEGG in the CC-MGO adducts and AHEs groups were mainly the following ten. Among them, PPAR and IL-17 signaling pathways are the major inflammatory pathways\u003csup\u003e41\u003c/sup\u003e. While AGEs induce cytotoxicity mainly by binding to their receptor RAGE and activating downstream cell signaling, thus inducing overexpression of inflammatory factors and triggering cytotoxicity. Therefore, we hypothesized that CC-MGO adducts alleviate AGEs-induced cytotoxicity by affecting PPAR and IL-17 signaling pathways. Based on the differential genes enriched by KEGG, we found that SLC27A5 was up-regulated and PCK1 and MMP1 genes were significantly down-regulated in the PPAR pathway, while the differential genes MMP1 and FOSB were both down-regulated in the IL-17 signaling pathway. Subsequent RT-PCR experiments were performed to further validate our transcription results.\u003c/p\u003e\n\u003cp\u003eTo validate the involvement of the AGE-RAGE signaling pathway in AGEs toxicity, as suggested by KEGG enrichment, we performed RT-qPCR analysis comparing the expression of key pathway genes between the Control (CK) and AGEs groups. In the RT-PCR experiments(Figure 9A) depicted in Figure 8C, the expression levels of CXCL8, CCL2, SERPINE1, IL1A, PIK3CD, NOS3, and AKT3 were found to be up-regulated in the AGEs group, whereas the expression of EDN1, EGR1, AGT, and TGFB2 was down-regulated. Notably, IL1A, an inflammatory factor belonging to the interleukin family, is known to regulate inflammation effectively. The elevated expression of IL1A suggests that the addition of AGEs leads to increased levels of inflammatory expression in Caco-2 cells, contributing to cytotoxicity\u003csup\u003e42\u003c/sup\u003e. Moreover, the decreased expression of EGR1, an essential early growth response protein that controls tumor cell growth and proliferation, following incubation with AGEs indicates the inhibition of normal cell growth, potentially leading to apoptosis\u003csup\u003e43\u003c/sup\u003e. The expression patterns of other genes also suggest their relevance to AGEs-induced cytotoxicity. Overall, AGEs can induce Caco-2 cytotoxicity by affecting the AGE-RAGE signaling pathway.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo validate the predicted involvement of the PPAR and IL-17 signaling pathways in CC-MGO adducts-mediated cytoprotection (based on GO/KEGG), we performed RT-qPCR analysis comparing the expression of key genes within these pathways between the AGEs group and the group co-treated with AGEs and CC-MGO adducts. As depicted in Figure 9D, SLC27A5 exhibited significant up-regulation, whereas MMP1, PCK1, and FOSB expression was markedly decreased in Caco-2 cells following pre-incubation with CC-MGO adducts.\u003c/p\u003e\n\u003cp\u003eThe observed up-regulation of SLC27A5 is noteworthy, considering its significant under-expression in hepatocellular carcinoma tissues. Conversely, high-level expression of PCK1 has been linked to diabetes promotion\u003csup\u003e44\u003c/sup\u003e, overexpression of MMP1 is associated with tumorigenesis and metastasis\u003csup\u003e45\u003c/sup\u003e, and increased FOSB expression has been implicated in gastric carcinogenesis\u003csup\u003e46\u003c/sup\u003e. These findings suggest that CC-MGO adducts may further alleviate AGEs-induced cytotoxicity by modulating the expression of these genes and influencing the activation of PPAR and IL-17 pathway transduction (Figure 9B).\u003c/p\u003e\n\u003cp\u003eTranscriptomic analysis indicated that AGEs-induced cytotoxicity was mainly mediated by the AGE-RAGE signaling pathway, with significant upregulation of inflammatory genes such as CXCL8 and CCL2 (Figure 9C). In contrast, CC-MGO adducts exerted protective effects via distinct mechanisms, as KEGG enrichment identified PPAR and IL-17 pathways (Figure 9D). Notably, upregulation of SLC27A5 and PCK1 suggested PPAR activation, enhancing metabolic and antioxidant capacity, while downregulation of MMP1 and FOSB implied suppression of IL-17-mediated inflammation. Since PPAR activation antagonizes NF-\u0026kappa;B signaling, a key downstream effector of RAGE, these results indicate that CC-MGO adducts do not simply reverse AGEs-induced changes but instead activate complementary protective pathways. Collectively, the findings suggest that CC-MGO adducts mitigate AGEs toxicity by enhancing metabolic resilience and limiting inflammatory responses through PPAR and IL-17 signaling, thereby counteracting RAGE-driven pathological processes including oxidative stress and metabolic disruption.\u003c/p\u003e\n\u003cp\u003eKEGG analysis revealed significant enrichment of the AGE-RAGE signaling pathway, with key genes (CXCL8, CCL2, IL1A, SERPINE1, PIK3CD, NOS3, AKT3, EDN1, EGR1, AGT, TGFB2) upregulated, highlighting RAGE activation as the main driver of AGEs-induced cytotoxicity in Caco-2 cells. These genes regulate inflammation, oxidative stress, endothelial dysfunction, and fibrosis\u0026mdash;hallmarks of RAGE signaling. Although RAGE protein levels and downstream phosphorylation (e.g., NF-\u0026kappa;B, MAPKs) were not directly assessed, the cytoprotective effects of CC-MGO adducts suggest functional activity despite limited intestinal absorption. Protection may arise from: Ⅰ. direct scavenging of reactive carbonyl species (e.g., MGO) and ROS in the intestinal lumen or at the cell surface, thereby reducing initial cellular damage\u003csup\u003e19,47\u003c/sup\u003e; Ⅱ. inhibition of receptor-mediated signaling pathways, such as AGE-RAGE interactions; and Ⅲ. activation of intracellular protective mechanisms, such as the Nrf2 antioxidant pathway, potentially by a small fraction of absorbed CC-MGO adducts or their intracellularly generated active components (e.g., liberated CC or its metabolites), as supported by our transcriptomic data.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study identified CC adducts with MGO, GO, and 5-HMF using LC-MS/MS, and successfully isolated CC-MGO adducts by HSCCC. Structural analysis revealed that CC-MGO forms via electrophilic substitution between MGO carbonyl groups and the CC benzene ring, while retaining phenolic hydroxyls and antioxidant properties. Antioxidant assays and food models (lactose/lysine, milk) confirmed that CC-MGO significantly inhibited AGEs formation. In Caco-2 cells, CC-MGO alleviated AGEs-induced cytotoxicity. Transcriptomic and RT-PCR analyses showed that AGEs toxicity involved AGE-RAGE signaling (e.g., CXCL8, CCL2, SERPINE1, IL1A), while CC-MGO mitigated damage through modulation of PPAR and IL-17 pathways (e.g., SLC27A5 upregulation, MMP1 and PCK1 downregulation). Overall, CC inhibits AGEs not only by trapping carbonyls but also via bioactive CC-MGO adducts, which further suppress AGEs toxicity in food and cellular systems. These findings provide a scientific basis for developing natural inhibitors of AGEs.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003eMaterials\u003c/h2\u003e\n \u003cp\u003eCC, MGO (40% aqueous solution, w/w), GO (40% aqueous solution, w/w), 5-HMF (\u0026ge;\u0026thinsp;95%), lactose (comprising 30% \u0026alpha;-lactose and 70% \u0026beta;-lactose). L-lysine (98%), o-phenylenediamine (OPD, \u0026ge; 98%) and 2,3-dimethylquinoxaline (DQ, \u0026ge; 97%) were sourced from Shanghai Maclean Biochemical Technology Co. Milk was provided by Inner Mongolia Meng Niu Dairy (Group) Co., Ltd. Penicillin (100 U/mL), streptomycin (100 ug/mL) were acquired from Greiner. DMEM medium was made available from Hyclone. Fetal Bovine Serum was obtained from Gibco. Cell Counting Kit-8 was purchased from Shanghai Beyotime Biotechnology Co.. The Caco-2 cells were kindly provided by the Oil Crops Research Institute (OCRI) of the Chinese Academy of Agricultural Sciences, Wuhan, Hubei Province, China.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eThe preparation of CC-MGO adducts\u003c/h3\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eMeasurement of MGO, GO and 5-HMF trapping capacity by CC\u003c/h2\u003e\n \u003cp\u003eThe trapping capacities of MGO, GO, and 5-HMF by CC (5 mM) were assessed in triplicate according to a published method with modifications\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. All solutions were prepared in 50 mM PBS (pH 7.4). Reaction mixtures (0.5 mL total volume) contained either MGO, GO, or 5-HMF (0.25 mL of 5 mM) with an equal volume of either PBS (control groups) or CC (5 mM, sample groups). After incubation (37\u0026deg;C, 1 h) and quenching on ice, 0.125 mL of OPD (20 mM) and the internal standard DQ (5 mM) were added. Derivatization proceeded for 30 min (MGO/GO) or 5 min (5-HMF). Samples were then filtered (0.22 \u0026micro;m) and analyzed by HPLC under conditions adapted from Wu et al\u003csup\u003e49\u003c/sup\u003e for MGO/GO and Teixid\u0026oacute; E et al\u003csup\u003e50\u003c/sup\u003e for 5-HMF.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eStructural identificationof CC adducts with MGO, GO, and 5-HMF\u003c/h2\u003e\n \u003cp\u003eThe adduct samples were diluted 100-fold, and then they underwent detection using LC-MS/MS\u003csup\u003e51\u003c/sup\u003e. The mass spectra were acquired using Electrospray Ionization (ESI) in negative ion mode. The capillary voltage was maintained at 3 kV, and the fragment voltage was set at 70 V. The atomization pressure was set to 40 psi, and the dry gas temperature was set at 300\u0026deg;C. The mass spectrometry ion range was scanned from 50 to 800 \u003cem\u003em/z\u003c/em\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eEffect of separation methods on the relative content of CC-MGO adducts\u003c/h2\u003e\n \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\n \u003ch2\u003eSemi-preparative liquid chromatography\u003c/h2\u003e\n \u003cp\u003eThe semi-preparative liquid phase was prepared using the method described by Liu et al. with some modifications. The column was Diamonsil TM-C18 (4.6\u0026times;200 mm, 5 \u0026micro;m). Mobile phase A was used 0.1% formic acid aqueous solution, and Mobile phase B was absolute methanol. The gradient elution process was used: 10% B at 0 min, 15% B at 2 min, 20% B at 5 min, 20% B at 15 min, 25% B at 17 min, 25% B at 21 min, 90% B at 22 min, 90% B at 24 min, 10% B at 28 min, and 10% B at 40 min. The target product was monitored at 273 nm and collected for structural identification and subsequent testing.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eHigh-speed counter-current chromatography\u003c/h2\u003e\n \u003cp\u003eThe HSCCC was prepared using the method described by Bito et al. with some modifications\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. The solvent system selected for pre-separation was n-butanol-ethyl acetate-water (1:14:15, v/v/v). Following the degassing treatment, the reaction mixture of CC and MGO was subjected to vacuum freeze-drying, as described previously, to obtain the crude sample. Before injection, the circulating water bath was turned on, and the temperature was set to 25℃. The flow rate of the stationary phase was set to 5 mL/min. The rotational speed was 900 r/min. The mobile phase was pumped into the system at a 1 mL/min flow rate. The detection wavelength was set at 280 nm.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003eImpact of CC-MGO adducts on AGEs formation in simulated food system\u003c/h2\u003e\n \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\n \u003ch2\u003eAntioxidant analysis of CC-MGO adducts\u003c/h2\u003e\n \u003cdiv id=\"Sec18\" class=\"Section4\"\u003e\n \u003ch2\u003eDPPH free radical scavenging ability\u003c/h2\u003e\n \u003cp\u003eThe DPPH free radical scavenging capacity of CC-MGO adducts was determined according to the method of Wu et al. with some modifications\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. The antioxidant activity of each sample was calculated as follows. Preparation of DPPH detection samples: Prepare CC-MGO adducts samples with deionized water at the following concentrations: 1, 2, 3, 4, and 5 mM. Mix CC-MGO adducts (0.2 mL) or 0.2 mL deionized water (blank) at different concentrations with 3.8 mL of 0.1 mM DPPH ethanol solution.\u003c/p\u003e\n \u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\u003cimg src=\"https://myfiles.space/user_files/58895_8739fc6c57c1c19a/58895_custom_files/img1768392957.png\" width=\"612\" height=\"91\"\u003e\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eAmong them, A represented the absorbance at 517 nm of the mixture containing the CC-MGO adducts and DPPH-ethanol solution. Ab represented the absorbance at 517 nm of the CC-MGO adducts alone (without DPPH). A0 represented the absorbance at 517 nm of the DPPH-ethanol solution.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003ch2\u003eABTS\u003csup\u003e+\u003c/sup\u003e radical scavenging ability\u003c/h2\u003e\n \u003cp\u003eThe ABTS⁺ radical scavenging capacity was evaluated using a reported method\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. The ABTS⁺ stock solution was generated by reacting equal volumes of 7.4 mM ABTS and 2.6 mM potassium persulfate in the dark at room temperature for 12 h. The working solution was then diluted with deionized water to an absorbance of 0.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02 at 734 nm. Antioxidant activity was calculated as follows:\u003c/p\u003e\n \u003cdiv id=\"Equb\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\u003cimg src=\"https://myfiles.space/user_files/58895_8739fc6c57c1c19a/58895_custom_files/img1768392988.png\" width=\"558\" height=\"72\"\u003e\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eAmong them, A represented the absorbance at 517 nm of the sample with ABTS\u003csup\u003e+\u003c/sup\u003e. A\u003csub\u003e0\u003c/sub\u003e represented the absorbance at 517 nm of ABTS\u003csup\u003e+\u003c/sup\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n \u003ch2\u003eEffect of lysine concentration on AGEs inhibition by CC-MGO adducts in simulated food systems\u003c/h2\u003e\n \u003cp\u003eLactose (60 mM) and L-lysine at different molar ratios (lactose:lysine\u0026thinsp;=\u0026thinsp;1:1 to 5:1) were prepared in 0.02 M PBS (pH 7.4). The CC-MGO adducts solution (5 mM) was added at a 1:1:1 volume ratio with lactose and lysine solutions. Control groups used PBS instead of the adduct solution. After vortexing, samples were heated at 98\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C for 1 h. Fluorescence was measured at Ex/Em\u0026thinsp;=\u0026thinsp;370/440 nm.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\n \u003ch2\u003eInfluence of CC-MGO adducts on AGEs formation in simulated and milk food systems\u003c/h2\u003e\n \u003cp\u003eThe influence of CC-MGO adducts on AGEs formation was evaluated in both simulated and milk systems. In the simulated system, lactose (60 mM) and L-lysine (20 mM) were incubated with CC-MGO adducts or aminoguanidine hydrochloride (AG) (1\u0026ndash;5 mM) in PBS. In the milk system, CC-MGO or AG (1\u0026ndash;5 mM) was directly added. Blank controls received no additives. The simulated system was processed using the aforementioned method, and the milk system was heated at 65\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C for 30 min\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. After reaction, fluorescence of specific AGEs (AGEs, pentosidine, argpyrimidine, crossline, vesperlysine) was measured\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\n \u003ch2\u003eInhibitory effect of CC-MGO adducts on AGEs induced cytotoxicity\u003c/h2\u003e\n \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\n \u003ch2\u003eCell viability assay of MGO and CC-MGO adducts\u003c/h2\u003e\n \u003cp\u003eThe cytotoxicity of MGO and CC-MGO adducts was assessed using a CCK-8 assay. Cells were seeded in 96-well plates at 1 \u0026times; 10⁴ cells/well and cultured for 24 h. Filter-sterilized samples were diluted in complete medium to concentrations ranging from 50 to 2000 \u0026micro;mol/mL. Then, 100 \u0026micro;L of each sample was added to the wells, with six replicates per concentration, using medium as the negative control. After 24 h of incubation, 10 \u0026micro;L of CCK-8 solution was added to each well and incubated for another 1.5 h at 37\u0026deg;C. Absorbance was measured at 450 nm using a microplate reader (Thermo, USA). Cell viability was calculated as follows:\u003c/p\u003e\n \u003cdiv id=\"Equc\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\u003cimg src=\"https://myfiles.space/user_files/58895_8739fc6c57c1c19a/58895_custom_files/img1768393025.png\" width=\"456\" height=\"99\"\u003e\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003ewhere A\u003csub\u003esample\u003c/sub\u003e is the absorbance of the sample, A\u003csub\u003econtrol\u003c/sub\u003e is the absorbance of the negative control (cells with medium), and A\u003csub\u003eblank\u003c/sub\u003e is the absorbance of the solvent blank (medium only).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\n \u003ch2\u003eRole of CC-MGO adducts on AGEs-induced cytotoxicity\u003c/h2\u003e\n \u003cp\u003eAGEs were generated using bovine serum albumin and MGO, and characterized by free amino group content and fluorescence spectroscopy\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eCytotoxicity was evaluated via CCK-8 assay. Various concentrations of AGEs (5\u0026ndash;40 mg/mL) were tested to establish a cytotoxic model. To assess protection, cells were pre-treated with CC-MGO adducts for 12 h, washed with PBS, and then exposed to AGEs for 24 h. Cell viability was measured using the CCK-8 assay, with blank (untreated) and control (AGEs-only) groups included for comparison.\u003c/p\u003e\n \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\n \u003ch2\u003eTranscriptome sequencing\u003c/h2\u003e\n \u003cp\u003eTranscriptome sequencing was performed on extracted tissue RNA. Poly(A) mRNA was enriched using oligo (dT) beads and fragmented. cDNA was synthesized from the fragmented mRNA and PCR-amplified to construct sequencing libraries.\u003c/p\u003e\n \u003cp\u003eAfter quality control, reads were aligned and analyzed for gene expression, variants, novel transcripts, SNPs, and gene structure optimization. Differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\n \u003ch2\u003eRT-PCR\u003c/h2\u003e\n \u003cp\u003eCaco-2 cells were cultured in a 6-well plate for 24 hours following treatment with diluted digestive fluid (50-fold dilution) that had been filtered using a centrifugal ultrafiltration tube to remove digestive enzymes. Reverse transcription was performed with the first-strand cDNA synthesis kit. The reverse transcription process involved pre-denaturation at 95\u0026deg;C for 3 min, denaturation at 95\u0026deg;C for 10 s, annealing at 58\u0026deg;C for 30 s, extension at 72\u0026deg;C for 30 s, and 40 cycles of amplification. Threshold cycle (CT) values were utilized to calculate mRNA expression. For each sample, the ∆CT(sample) value was determined by calculating the difference between the CT value of the target gene and the CT value of the \u0026beta;-actin inner reference gene. Expression levels relative to the control were estimated by calculating ∆∆CT (∆CT(sample)- ∆CT(control)) and then using the 2\u003csup\u003e\u0026minus;∆∆CT\u003c/sup\u003e method\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. The primer design is shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e\n \u003ch2\u003eData analysis\u003c/h2\u003e\n \u003cp\u003eThe data obtained from the experiments were subjected to statistical analysis using IBM SPSS Statistics 21 software. The results were then expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Comparisons of means between multiple groups were performed by one-way one-way ANOVA (OneWay ANOVA), and multiple comparisons between groups were performed using Duncan\u0026apos;s test if there was a significant difference between groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Plotting was done using Origin 8.0 software.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eABTS: 2,2\u0026apos;-Azinobis- (3-ethylbenzthiazoline-6-sulphonate); AGEs: Advanced glycation end products; BSA: Bovine albumin; CC: Catechin; CHAs: CC\u0026amp;5-HMF adducts; CCK8: Cell Counting Kit-8; CEL: NƐ-carboxyethyl lysine; CGAs: CC\u0026amp;GO adducts; CML: NƐ-carboxymethyl lysine; DPPH: 1,6- Bis (diphenylphosphino) hexane; DQ: 2, 3-Dimethylquinoxaline; GO: Glyoxal; HSCCC: High-speed counter- current chromatography; MGO: Methylglyoxal; MR: Maillard reaction; OPD: O-Phenylenediamine; RCS: Reactive carbonyl species; ROS: Reactive oxygen species; 5-HMF: 5-hydroxymethylfurfural.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJia Yan\u003c/strong\u003e: Conceptualization, visualization and writing \u0026ndash; review \u0026amp; editing. \u003cstrong\u003eJiangying Tan\u003c/strong\u003e: Data curation and writing original draft. \u003cstrong\u003eXingyu Zhang\u003c/strong\u003e: Investigation and methodology. \u003cstrong\u003eChenxu Bao\u003c/strong\u003e: Investigation and visualization. \u003cstrong\u003eChen Zhou\u003c/strong\u003e: Conceptualization and methodology. \u003cstrong\u003eBoqian He\u003c/strong\u003e: Conceptualization and data curation. \u003cstrong\u003eYinxin Li\u003c/strong\u003e: Conceptualization and methodology. \u003cstrong\u003eBaiyi Lu\u003c/strong\u003e: Supervision.\u003cstrong\u003e\u0026nbsp;Lianliang Liu\u003c/strong\u003e: Supervision. \u003cstrong\u003eFan Yi\u003c/strong\u003e: Supervision. \u003cstrong\u003eQian Wu\u003c/strong\u003e: Conceptualization, funding acquisition and supervision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was financially supported by National Natural Science Foundation of China (No. 32472341), the Open Fund of Key Laboratory for Quality Evaluation and Health Benefit of Agro-Products, Ministry of Agriculture and Rural Affairs (ZJU-APQHLAB-2406), Natural Science Foundation of Hubei Province (2024AFD281), Hubei Provincial Natural Science Foundation for Distinguished Young Scholars (JCZRJQ202500133), Science and Technology Research Project of Education Department of Hubei Province (No. F2023006).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSchalkwijk, C. 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Inhibition of Advanced Glycation End-Product Formation by High Antioxidant-Leveled Spices Commonly Used in European Cuisine. \u003cem\u003eAntioxidants (Basel)\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, doi:10.3390/antiox8040100 (2019).\u003c/li\u003e\n\u003cli\u003eWu, Q.\u003cem\u003e et al.\u003c/em\u003e Inhibition of advanced glycation endproducts formation by lotus seedpod oligomeric procyanidins through RAGE-MAPK signaling and NF-\u0026kappa;B activation in high-AGEs-diet mice. \u003cem\u003eFood Chem Toxicol\u003c/em\u003e \u003cstrong\u003e156\u003c/strong\u003e, 112481, doi:10.1016/j.fct.2021.112481 (2021).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Real-time quantitative PCR primer design\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"97%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eGene name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003ePrimer base design\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eEDN1-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eTCTCTCTGCTGTTTGTGGCTTGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eEDN1-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eGGTGGACTGGGAGTGGGTTTCT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eAGT-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eTGGATGTTGCTGCTGAGAAGATTGA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eAGT-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eCTTGGAAGTGGACGTAGGTGTTGAA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eTGFB2-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eTGCCATCCCGCCCACTTTCT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eTGFB2-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eGCCATTCGCCTTCTGCTCTTGT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eSERPINE1-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eTGGTGCTGGTGAATGCCCTCT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eSERPINE1-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eGTGCTGCCGTCTGATTTGTGGAA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003ePIK3CD-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eGACACCATCGCCAACATCCAACT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003ePIK3CD-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eCACAATAGCCAGCACAGGAGAGG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eCOL4A1-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eCCACAGGGACCACCAGGACAAA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eCOL4A1-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eTTCCAGCGAAACCAGGCAAGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eAKT3-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eCAGAACGACCAAAGCCAAACACATT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eAKT3-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eAGTCTGTCTGCTACAGCCTGGATAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eSLC27A5-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eGCAGCATGGCGTGACAGTGAT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eSLC27A5-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eGTTGCCTTCTGTGGAGCCGTAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eERG1-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eCACGAACGCCCTTACGCT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eERG1-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eCATCGCTCCTGGCAAACT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eCXCL8-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eCCACCGGAGCACTCCATAAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eCXCL8-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eGATGGTTCCTTCCGGTGGTT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eCCL2-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eTCTGTGCCTGCTGCTCATAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eCCL2-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eGGGCATTGATTGCATCTGGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eIL1A-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eAAGACAGTTCCTCCATTGAT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eIL1A-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eGATACTCAGAGACACAGATTG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eFOSB-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eCTTGTGCAACCCACCCTCA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eFOSB-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eGCCACTGCTGTAGCCACTCAT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eMMP1-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eGCTCATGAACTCGGCCATTCTCTTGGACT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eMMP1-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eCGGGTAGAAGGGATTTGTGCGCATGTA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003ePCK1-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eCGGAAAGAAACCTGTGGATCTC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003ePCK1-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eCAGATGTGGATGTGATCAGGCT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eNOS3-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eGTGATGGCGAAGCGAGTGAAGG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003eNOS3-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eTTACCACCAGCACCAGCGTCTC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026Beta;-actin-F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eCCTGACTGACTACCTCATGAAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 219px;\"\u003e\n \u003cp\u003e\u0026beta;-actin-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 701px;\"\u003e\n \u003cp\u003eGACGTAGCACAGCTTCTCCTTA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. The mass spectral information of CC-MGO adducts, CGAs and CHAs\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"890\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eAdducts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 202px;\"\u003e\n \u003cp\u003eAdduct name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003eMolecular formula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003ePeak time\u003c/p\u003e\n \u003cp\u003e(min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003eMolecular weight\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(\u003cem\u003em/z\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003eParent ion\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003em/z\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003eInaccuracies\u003c/p\u003e\n \u003cp\u003e(ppm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003eIon fragment\u003c/p\u003e\n \u003cp\u003e(\u003cem\u003em/z\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 84px;\"\u003e\n \u003cp\u003eCC-MGO adducts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 202px;\"\u003e\n \u003cp\u003eMono CC-mono MGO adduct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003eC\u003csub\u003e18\u003c/sub\u003eH\u003csub\u003e18\u003c/sub\u003eO\u003csub\u003e8\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e4.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e361.09289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e361.09268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e343.08206，289.07174，181.04971\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 202px;\"\u003e\n \u003cp\u003eMono CC-di MGO adduct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003eC\u003csub\u003e21\u003c/sub\u003eH\u003csub\u003e22\u003c/sub\u003eO\u003csub\u003e10\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e4.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e433.11402\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e433.11337\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e415.10324，361.09268，343.08206，263.05576\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 202px;\"\u003e\n \u003cp\u003eDi CC-mono MGO adduct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003eC\u003csub\u003e33\u003c/sub\u003eH\u003csub\u003e32\u003c/sub\u003eO\u003csub\u003e14\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e4.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e651.17193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e651.17188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e361.09268，343.08206，289.07174，245.08145，181.04970\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 202px;\"\u003e\n \u003cp\u003eDi CC-di MGO adduct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003eC\u003csub\u003e36\u003c/sub\u003eH\u003csub\u003e36\u003c/sub\u003eO\u003csub\u003e16\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e4.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e723.19306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e723.19299\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e361.09268，289.07174，245.08145，181.04970\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 84px;\"\u003e\n \u003cp\u003eCGAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 202px;\"\u003e\n \u003cp\u003eMono CC-mono GO adduct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003eC\u003csub\u003e17\u003c/sub\u003eH\u003csub\u003e16\u003c/sub\u003eO\u003csub\u003e8\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e3.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e347.07724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e347.07675\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e289.07174，245.08145，205.04953，167.03365，123.04401，109.02809\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 202px;\"\u003e\n \u003cp\u003eDi CC-mono GO adduct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003eC\u003csub\u003e32\u003c/sub\u003eH\u003csub\u003e30\u003c/sub\u003eO\u003csub\u003e14\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e3.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e637.15628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e637.15588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e347.07675，289.07174，245.08145，205.04953，167.03365，123.04401，109.02809\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 202px;\"\u003e\n \u003cp\u003eDi CC-di GO adduct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003eC\u003csub\u003e34\u003c/sub\u003eH\u003csub\u003e32\u003c/sub\u003eO\u003csub\u003e16\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e3.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e695.16176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e695.16144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e289.07174，245.08145，167.03365，109.02809\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003eCHAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 202px;\"\u003e\n \u003cp\u003eMono CC-mono 5-HMF adduct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003eC\u003csub\u003e21\u003c/sub\u003eH\u003csub\u003e20\u003c/sub\u003eO\u003csub\u003e9\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e415.10346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e415.10306\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e289.07174，245.08145，205.04953，167.03365，123.04401，109.02809\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 202px;\"\u003e\n \u003cp\u003eMono CC-di 5-HMF adduct\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003eC\u003csub\u003e21\u003c/sub\u003eH\u003csub\u003e20\u003c/sub\u003eO\u003csub\u003e9\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e4.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e541.13515\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e541.13495\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 97px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003e289.07174，245.08145，123.04401\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Annotation table of GO function of differential genes between CK group and AGEs group (TOP 10)\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 320px;\"\u003e\n \u003cp\u003eGo second level annotation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 183px;\"\u003e\n \u003cp\u003eTypes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 292px;\"\u003e\n \u003cp\u003eName\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003eGene count\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 320px;\"\u003e\n \u003cp\u003eGO0009987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 183px;\"\u003e\n \u003cp\u003eBiological process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 292px;\"\u003e\n \u003cp\u003eCellularprocess\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e324\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 320px;\"\u003e\n \u003cp\u003eGO0005488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 183px;\"\u003e\n \u003cp\u003eMolecular function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 292px;\"\u003e\n \u003cp\u003eBinding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e308\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 320px;\"\u003e\n \u003cp\u003eGO0044699\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 183px;\"\u003e\n \u003cp\u003eBiological process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 292px;\"\u003e\n \u003cp\u003eSingle-organismprocess\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e262\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 320px;\"\u003e\n \u003cp\u003eGO0008152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 183px;\"\u003e\n \u003cp\u003eBiological process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 292px;\"\u003e\n \u003cp\u003eMetabolicprocess\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e228\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 320px;\"\u003e\n \u003cp\u003eGO0065007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 183px;\"\u003e\n \u003cp\u003eBiological process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 292px;\"\u003e\n \u003cp\u003eBiologicalregulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e228\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 320px;\"\u003e\n \u003cp\u003eGO0050789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 183px;\"\u003e\n \u003cp\u003eBiological process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 292px;\"\u003e\n \u003cp\u003eRegulationofbiologicalprocess\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 320px;\"\u003e\n \u003cp\u003eG:0003824\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 183px;\"\u003e\n \u003cp\u003eMolecular function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 292px;\"\u003e\n \u003cp\u003eCatalyticactivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e206\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 320px;\"\u003e\n \u003cp\u003eGO0050896\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 183px;\"\u003e\n \u003cp\u003eBiological process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 292px;\"\u003e\n \u003cp\u003eResponsetostimulus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 320px;\"\u003e\n \u003cp\u003eGO0005623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 183px;\"\u003e\n \u003cp\u003eCellular composition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 292px;\"\u003e\n \u003cp\u003eCell\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 320px;\"\u003e\n \u003cp\u003eGO0044464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 183px;\"\u003e\n \u003cp\u003eCellular composition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 292px;\"\u003e\n \u003cp\u003eCellpart\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Annotated Table of Differential Gene GO Functions between AGEs Group and CMAs Group (TOP 10)\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eGo second level annotation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eTypes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eName\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003eGene count\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eGO0005488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eMolecular function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eBinding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eGO0009987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eBiological process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eCellular process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eGO0008152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eBiological process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eMetabolic process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eGO0044699\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eBiological process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eSingle-organism process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eGO0003824\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eMolecular function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eCatalytic activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eGO0005623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCellular composition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eCell\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eGO0044464\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCellular composition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eCell part\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eGO0043226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eCellular composition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eOrganelle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eGO0050789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eBiological process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eRegulation of biological process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eGO0065007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eBiological process\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eBiological regulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5. Differentially expressed gene KEGG between CK group and AGEs group\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003ePathway ID\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003ePathway description\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eGene count\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003emap04668\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eTNF signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003emap04064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eNF-\u0026kappa;B signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003emap00010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eGlycolysis / Gluconeogenesis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003emap02010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eABC transporters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003emap04010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eMAPK signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003emap04657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eIL-17 signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003emap04151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003ePI3K-Akt signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003emap04630\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eJAK-STAT signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003emap04933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eAGE-RAGE signaling pathway in diabetic complications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003emap04350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eTGF-beta signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6. Differentially expressed gene KEGG between AGEs group and CMAs group\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003ePathway ID\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003ePathway description\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003eGene count\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003emap03320\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003ePPAR signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003emap05020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003ePrion disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003emap00010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003eGlycolysis / Gluconeogenesis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003emap04657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003eIL-17 signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003emap04974\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003eProtein digestion and absorption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003emap04931\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003eInsulin resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003emap00120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003eBile acid metabolism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003emap04371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003eApelin signaling pathway\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003emap04964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003eProximal tubule bicarbonate reclamation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 24px;\"\u003e\n \u003cp\u003emap00020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003eCitrate cycle (TCA cycle)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Catechin (CC), Methylglyoxal (MGO), Advanced glycation end products (AGEs), High-speed counter-current chromatography (HSCCC), Transcriptomics","lastPublishedDoi":"10.21203/rs.3.rs-8521410/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8521410/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAdvanced glycation end products (AGEs) are significant byproducts of the Maillard reaction and are implicated in degenerative diseases. Catechin (CC), a dietary polyphenol distributed in fruits and vegetables, inhibits AGEs formation through binding with carbonyl compounds. However, the biological role of these binding adducts remains unclear. This study first isolated the major CC-methylglyoxal (MGO) adducts using high-speed counter-current chromatography. Structural analysis confirmed it retains antioxidant phenolic hydroxyls. In food models (lactose/lysine and milk), CC-MGO significantly inhibited AGEs formation via antioxidant activity. In Caco-2 cells, CC-MGO alleviated AGEs-induced cytotoxicity. Transcriptomics revealed AGEs activated the AGE-RAGE pathway (upregulating CXCL8, CCL2), while CC-MGO counteracted toxicity by modulating PPAR and IL-17 pathways, specifically upregulating SLC27A5 and downregulating MMP1 and PCK1. These findings demonstrate that catechin not only scavenges carbonyls but also forms bioactive adducts that further suppress AGEs formation and toxicity, providing a dual mechanism for natural intervention.\u003c/p\u003e","manuscriptTitle":"A novel perspective on the amelioriating effects of catechin-carbonyl adducts on AGEs toxicity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-14 12:29:09","doi":"10.21203/rs.3.rs-8521410/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d1ae5045-5a6b-4cba-9672-e53d19e4bb9a","owner":[],"postedDate":"January 14th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":60993080,"name":"Biological sciences/Biochemistry"},{"id":60993081,"name":"Biological sciences/Chemical biology"},{"id":60993082,"name":"Biological sciences/Drug discovery"}],"tags":[],"updatedAt":"2026-03-02T10:25:48+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-14 12:29:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8521410","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8521410","identity":"rs-8521410","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}