1. Introduction
Obesity is a health issue characterized by the excessive accumulation of adipose tissue rich in triglycerides, resulting from an imbalance between energy intake and expenditure. The primary causes of obesity include overconsumption of high-calorie, high-fat foods and a sedentary lifestyle, leading to an abnormal accumulation of body fat [
1]. Furthermore, obesity is associated with inflammation in adipose tissue, contributing to metabolic dysfunction. Inflammatory mechanisms are pivotal in linking obesity to metabolic diseases [
2]. The inflammation in adipose tissue exacerbates metabolic dysfunction and is a critical factor in the progression of obesity-related complications [
3]. Additionally, obesity is linked to changes in the gut microbiota, which further promote inflammation and metabolic issues [
4]. Obesity is not merely a cosmetic concern but is closely linked with the onset of various chronic non-communicable diseases (NCDs). Recent studies from 2022 to 2024 have reinforced the association between obesity and a range of NCDs, including hypertension, hyperlipidemia, type 2 diabetes, cardiovascular disease, stroke, arthritis, atherosclerosis, certain cancers, metabolic syndrome, sleep apnea, osteoarthritis, and lower back pain. These studies highlight the significant role of obesity as a critical risk factor for the development and progression of these chronic conditions [
5,
6]. Thus, reducing body fat and alleviating the associated insulin resistance play crucial roles in the treatment and prevention of obesity-related comorbidities.
Recent studies over the past five years have consistently demonstrated that weight loss significantly reduces the risk of obesity-related complications and chronic diseases. Weight loss has been shown to improve outcomes in conditions such as type 2 diabetes, cardiovascular disease, hypertension, and metabolic syndrome, highlighting the critical importance of weight management in mitigating the health impacts of obesity [
7,
8,
9,
10]. Various interventions are available to aid weight reduction, including dietary adjustments, regular exercise, behavioral modification programs, obesity surgery, and pharmacological treatments [
11,
12,
13]. Recent meta-analyses within the past five years have shed light on the efficacy and limitations of anti-obesity drugs. These interventions have garnered attention for their notable compliance rates and short-term effectiveness in reducing obesity levels. However, meta-analytical findings underscore the necessity for cautious consideration due to the presence of significant side effects. While these drugs may offer promising results in the short run, their long-term viability and safety profile warrant thorough scrutiny. For instance, studies have highlighted adverse effects such as gastrointestinal discomfort, cardiovascular complications, and neurological disturbances associated with certain anti-obesity medications. Therefore, while these drugs may represent a viable option for some individuals, their widespread use is curtailed by the need for careful risk–benefit assessment and ongoing monitoring of adverse reactions [
14,
15]. While the use of anti-obesity drugs is often limited by side effects, there is increasing interest in the therapeutic potential of specific hormonal treatments that target underlying metabolic processes. Among these, GLP-1 receptor agonists stand out due to their multifaceted role in regulating appetite and glucose metabolism, which not only enhances their effectiveness but also potentially mitigates the severity of side effects commonly associated with other pharmacological treatments.
Glucagon-like peptide-1 (GLP-1) is an incretin hormone composed of 30 or 31 amino acids that plays a pivotal role in glucose homeostasis and body weight regulation. GLP-1 enhances insulin secretion from pancreatic beta cells while decreasing glucagon levels. In addition to its effects on insulin and glucagon, GLP-1 exhibits a wide range of actions, including promoting insulin sensitivity in the adipose tissue, stimulating energy expenditure and fat breakdown, reducing hepatic steatosis and liver lipid content, and delaying gastric emptying. These combined effects lead to weight loss by increasing satiety and reducing food intake by the brain [
16,
17,
18]. Numerous animal studies and clinical trials have demonstrated the effectiveness of stimulating GLP-1 secretion for the treatment and prevention of obesity [
19,
20,
21]. Consequently, drugs that induce GLP-1 secretion have emerged as promising therapeutic agents for the treatment of obesity.
Lycium chinense Mill (LCM), belonging to the Solanaceae family, is a deciduous shrub commonly known as wolfberry. In Korean traditional medicine, LCM is known for its ability to purify blood, relieve symptoms of body heat, clear the lungs, and reduce irritability. Among these properties, the ability to nurture vital energy is of particular interest in modern medicine, and has led to research in areas such as depression, diabetes, and inflammation [
22,
23,
24]. However, existing research on LCM was mainly focused on diabetes, including the anti-diabetic effect of Indongdeungjigolpi-tang [
25] and the anti-diabetic effect of LCM and Cornus officinalis extract [
24]. Research on GLP-1 initially focused on anti-diabetes, but the recent discovery of its anti-obesity effect shifted the focus of the research, which led us to the idea that LCM might also have an anti-obesity effect and prompted this study.
This study aimed to investigate the anti-obesity and anti-diabetic effects of LCM hot water extract by examining GLP-1 secretion in NCI-h716 cells, assessing lipid accumulation and expression of lipogenic and adipogenic factors in 3T3-L1 adipocytes, and analyzing the weight and biochemical changes induced by LCM treatment in a high-fat diet-induced model. This study aimed to scientifically validate the potential of LCM as a food or pharmaceutical material for the treatment of diabetes and obesity.
3. Discussion
Obesity is a multifactorial condition characterized by excessive fat production and accumulation, and is often attributed to the overconsumption of dietary fats [
1]. Obesity-related diseases such as diabetes are major causes of mortality in modern society, and excess nutrition has been linked to various types of cancer. Consequently, it is imperative to address the root cause of obesity, which is a precursor of numerous diseases. Conventional pharmacological treatments for obesity and related conditions such as hypertension, cardiovascular disease, constipation, fatty liver disease, and fat-soluble vitamin imbalances are associated with common side effects [
30,
31]. This has led to growing interest in the use and study of traditional herbal remedies as alternatives.
LCM, a member of the family Solanaceae, has been traditionally used in traditional Korean medicine to treat various health conditions, including diabetes and obesity. Classified by its cold and sweet nature, it is believed to target the lung, liver, and kidney meridians, helping to cool the blood, reduce steaming bone syndrome, clear lung heat, and alleviate symptoms such as night sweats and diabetic thirst [
32]. LCM has antidepressant, antioxidant, and hepatoprotective effects. In addition, LCM enhances innate immunity and mitigates acute inflammatory responses [
22]. Extracts of
Cordyceps militaris and
Eleutherococcus senticosus have been reported to regulate enzymes involved in glucose metabolism. Furthermore, LCM has demonstrated its ability to inhibit α-glucosidase and α-amylase, reduce postprandial blood glucose levels, and improve insulin sensitivity, thus proving its anti-obesity and glucose-lowering effects [
23]. Despite its known efficacy against various diseases and diabetes, existing research on LCM has only investigated blood composition, such as blood sugar and triglyceride, after administering medicinal ingredients [
24]. This was disappointing because it did not identify the mechanism. Moreover, there has been no research on whether hot water extracts of LCM can stimulate GLP-1 secretion from L-cells. Additionally, the detailed mechanisms contributing to its effectiveness in diabetes and obesity remain unclear.
Our study results demonstrate that LCM treatment significantly stimulates GLP-1 secretion in a concentration-dependent manner in NCI-h716 cells, without inducing cytotoxic effects up to a concentration of 250 μg/mL. These findings suggest a potential therapeutic role for LCM in regulating GLP-1 secretion, an important hormone involved in the regulation of glucose homeostasis and appetite control. We also investigated the key signaling molecules involved in GLP-1 secretion. The observed increase in the phosphorylation of the Protein Kinase A catalytic subunit (PKA C) and AMP-activated protein kinase (AMPK) upon LCM treatment suggests that these signaling pathways play a significant role in the mechanism by which LCM enhances GLP-1 secretion. PKA C is involved in the cAMP-dependent pathway, which is a classical pathway for regulating GLP-1 secretion [
33,
34]. Conversely, AMPK, a key energy sensor, has been implicated in glucose metabolism and insulin sensitization, which may be linked to enhanced GLP-1 secretion [
35] (
Figure 1).
Subsequently, we confirmed that treatment with LCM for 48 h did not induce cytotoxic effects at concentrations up to 250 μg/mL. Through the reduction in lipid droplet formation and absorbance in Oil Red O staining following LCM treatment, we observed that LCM could modulate lipid accumulation, a hallmark of adipocyte differentiation. Furthermore, the LCM-induced downregulation of key lipogenic factors, such as Fatty Acid Synthase (FAS), fatty acid-binding protein 4 (FABP4), and Sterol Regulatory Element-Binding Protein 1c (SREBP1c) induced by LCM treatment was verified at the protein expression level. These factors are crucial for the synthesis and storage of fatty acids in adipocytes, and their decreased expression likely contributed to the observed reduction in lipid accumulation. Moreover, FABP4 not only plays a role in lipid metabolism but is also significantly involved in inflammatory processes. Increased expression of FABP4 is associated with enhanced secretion of inflammatory cytokines such as TNF-α and IL-6, indicating its role in promoting inflammation [
36,
37,
38]. The downregulation of FABP4 upon LCM treatment suggests a potential dual benefit of LCM in both reducing lipid accumulation and modulating inflammatory responses, which are often interconnected in metabolic disorders. Additionally, the altered expression of the central transcription factors in adipocyte differentiation, CCAAT/Enhancer Binding Protein alpha (C/EBPα), and Peroxisome Proliferator-Activated Receptor gamma (PPARγ) suggests that LCM interferes with the essential transcriptional machinery for fat generation. Both C/EBPα and PPARγ are key regulators of adipogenesis, driving the expression of genes that promote adipocyte differentiation and lipid storage [
27]. Downregulation of these transcription factors following LCM treatment explains the observed inhibition of adipogenesis and lipogenesis (
Figure 2).
We investigated the effects of LCM in an HFD model to assess its effects on the body. The significant increase in body weight in the HFD group compared with that in the normal diet (ND) group by the eighth week confirmed the expected impact of a high-fat diet on weight gain. At this point, the oral administration of LCM at a dose of 250 mg/kg led to a gradual decrease in weight gain among these animals, showing a significant difference starting from the tenth week. Additionally, the visual differences in body images before dissection among the groups provided strong visual evidence of the impact of LCM on body composition. During the study, food intake was observed to be lower in the LCM group compared to the HFD group. This reduction in food intake could potentially be attributed to the increased secretion of GLP-1, known to suppress appetite by acting on the brain. While our in vitro experiments with NCI-h716 cells demonstrated that LCM treatment promotes GLP-1 secretion, it is crucial to note that we did not measure GLP-1 levels in our animal experiments. Therefore, while this hypothesis is plausible, further studies are necessary to directly confirm the involvement of GLP-1 in the observed effects on food intake and weight reduction. Furthermore, it should be noted that the food intake data presented are average values for each group. We did not measure individual food consumption, and the standard diet (ND group) was administered only PBS orally. Consequently, these data must be interpreted with caution (
Figure 3).
Our study contributes to our understanding of the metabolic effects of LCM on glucose homeostasis and lipid profiles in HFD-induced obesity. The results of the OGTT indicated that the administration of LCM markedly improved glucose tolerance in HFD-fed mice. This was evident from the quicker normalization of blood glucose levels in the LCM treatment group compared to the persistent hyperglycemia observed in the HFD group. Furthermore, the reduction in the AUC for OGTT in the LCM-treated group compared to that in the HFD group underscores the potential of LCM to mitigate glucose intolerance, a common metabolic derangement in obesity and type 2 diabetes. LCM could play a pivotal role in preventing the progression of metabolic syndrome components, considering the central role of glucose intolerance in their development. In terms of liver function, the analysis of serum AST and ALT levels provides insight into the hepato-protective effects of LCM. The significant reduction in AST levels following LCM treatment, aligning them with those in the ND group, suggests the potential of LCM to alleviate HFD-induced hepatocellular damage. However, the absence of significant changes in ALT levels across all groups indicates that further studies are required to fully understand the impact of LCM on liver function. Moreover, the improvements in the serum lipid profile observed with LCM treatment, particularly the reduction in TC and TG, highlight the beneficial effects of LCM in managing obesity-associated hyperlipidemia. Although changes in HDL-C and LDL-C levels were not statistically significant, the overall trend suggested a potential regulatory effect of LCM on lipid metabolism. These findings are particularly relevant given the critical role of dyslipidemia in the pathogenesis of cardiovascular diseases associated with obesity (
Figure 4).
Our findings highlight the significant protective effects of LCM against hepatic steatosis in a rodent model of HFD-induced simple steatosis. Visual and quantitative analyses of liver tissues from the LCM-treated group revealed noticeable reductions in lipid accumulation, darker liver coloration, and a decrease in liver weight and the size of lipid droplets. This suggests a reversal of fat accumulation and the potential mobilization of stored lipids within the liver. These changes closely mirrored those observed in the normal diet (ND) group, underscoring the therapeutic potential of LCM in mitigating the progression of liver diseases associated with excess diet. The administration of LCM not only resulted in darker liver coloration, indicative of reduced hepatic lipid accumulation, but also significantly reduced liver weight, which is often associated with hepatomegaly owing to excessive lipid storage. This suggests that LCM has a substantial protective effect against hepatic steatosis (
Figure 5).
Our research underscores the significant anti-obesity potential of LCM, which was shown to counteract the increase in white adipose tissue (WAT) mass and adipocyte hypertrophy in an HFD-induced model. Notably, LCM administration led to a substantial reduction in the masses of both epididymal and inguinal WAT, which are key indicators of adiposity and metabolic health risks. Furthermore, histological analysis revealed that LCM significantly decreased adipocyte size in HFD-fed mice, directly affecting adipocyte hypertrophy. Because excessive adipocytes are associated with insulin resistance, inflammation, and other metabolic disorders, the ability of LCM to reduce adipocyte size has profound implications for the management of obesity and related metabolic complications (
Figure 6).
To investigate the potential anti-diabetic and anti-obesity effects of the LCM extract, we detected a total of seven bioactive components in the LCM extract through LC-MS analysis (
Figure 7). Among these, compounds (1) 2,4-Pentadienoic acid, (2) 2′,5-dihydroxy-6,7,8,6′-tetramethoxy flavone, and (5) Coumarin 314 have not yet been studied extensively for their physiological efficacy, indicating areas for future research. Compound (3) Apigenin, a common dietary flavonoid found in various vegetables, medicinal herbs, and fruits, is known for its diverse physiological functions, including antiviral, anticancer, antibacterial, antioxidant, and anti-inflammatory properties, and blood pressure reduction. Notably, Apigenin has been reported to inhibit α-glucosidase activity, enhance insulin secretion, and neutralize reactive oxygen species, potentially preventing diabetes complications [
39]. Similarly, (4) Myricetin, a flavonoid present in various natural products, exhibits anti-inflammatory, anticancer, antiviral, and anti-obesity effects. It has been shown to regulate blood glucose levels and stimulate GLP-1 receptors, thereby reducing postprandial hyperglycemia. Moreover, Myricetin improves carbohydrate metabolism and reduces oxidative stress, enhancing overall glucose utilization and offering protection against diabetes-related complications [
40]. (6) Quercitrin also demonstrates anti-diabetic effects by increasing insulin secretion and improving carbohydrate metabolism. In particular, it has been reported to protect pancreatic β cells from inflammation and oxidative stress, thereby preventing diabetes complications [
41]. Lastly, (7) Liquiritigenin shows potential as a therapeutic agent for diabetes by increasing insulin secretion. It is particularly noted for enhancing cell survival and reducing cell apoptosis under lipotoxic conditions induced by palmitate in hepatocytes, suggesting its therapeutic potential in treating NAFLD, a complication associated with diabetes [
42]. These findings underscore the therapeutic potentials of the identified compounds in the LCM extract and highlight the need for further studies to fully understand their mechanisms and broader health implications in the context of diabetes and obesity.
4. Materials and Methods
4.1. Preparation of LCM Extract
LCM was purchased from Noah Herbal Pharmacy and subjected to extraction to prepare a water extract. Specifically, 100 g of LCM was mixed with 1 L of distilled water at a ratio of 10:1 (
w/
v) and heated at 100 °C for 2 h. After the heating process, the extract was filtered through a 20 µm filter to remove any particulate matter. The filtrate was then subjected to reduced-pressure filtration to concentrate the extract. The concentrated extract was freeze-dried to obtain a powdered form. The powder was dissolved in Phosphate-buffered saline (PBS) for experimental use. This extract was used for further in vitro and in vivo studies, as described in the subsequent sections. The method for the herbal extract was based on the following reference [
43].
4.2. Liquid Chromatography-Mass Spectrometry (LC-MS)
The extract was separated chromatographically using LC-MS, following the methodologies detailed in references [
44,
45]. Briefly, chromatographic separation was conducted on an Agilent 1290 Infinity LC System using a Walters C18 column at 30 °C. The mobile phase of 0.1% formic acid in water (A) and acetonitrile (B) followed a gradient from 5% to 95% B over 15 min, maintained at 95% B for 5 min, and then returned to 5% B over the next 5 min. Sample injections of 1 μL were performed via autosampler. The system was connected to an Agilent 6550 Accurate-Mass Q-TOF MS with a dual AJS ESI source, operating at 3500 V and capturing spectra from 100 to 1700
m/
z at a rate of 1 spectra/s. Analysis was completed using Mass Hunter Qualitative Analysis Software (version B.07.00).
4.3. Reagents
The lysis buffer and a cell fractionation kit were purchased from Cell Signaling Technology (Danvers, MA, USA). Dexamethasone (DEX), insulin, and IBMX were purchased from Sigma-Aldrich (St. Louis, MO, USA). Enhanced chemiluminescence (ECL) solution was obtained from DOGEN (Seoul, Republic of Korea). Antibodies for SREBP1c (SC-13551), β-actin (SC-47778), and secondary antibodies (sc-516102 and sc-2004) were purchased from Santa Cruz Biotechnology (Santa Cruz, San Francisco, CA, USA), and the other antibodies were purchased from Cell Signaling Technology (Beverly, MA, USA). These antibodies were as follows: FASN (3180s), FABP4(2120s), C/EBPα (8187s), PPAR γ (2435s), AMPK (2532s), phospho-AMPK (2535s), PKA C (4782s), and phospho-PKA C (4781s).
4.4. Cell Culture
Two cell lines, NCI-h716 and 3T3-L1, were used. NCI-h716 and 3T3-L1 cells were procured from the Korean Cell Line Bank and cultured in a 5% CO2, 37 °C cell incubator. The culture medium was supplemented with 10% fetal bovine serum (FBS) and 100 U/mL penicillin.
NCI-h716 cells were cultured in RPMI medium and maintained in a floating state. NCI-h716 cells were seeded in 12-well plates pre-coated with Matrigel using DMEM as the culture medium 3 d before the experiments. These cells were allowed to differentiate for 2 d and subsequently subjected to 16 h of serum starvation. Next, LCM prepared in 1 mM CaCl2-containing PBS according to the experimental conditions was added to the cells and incubated for 2 h. The culture medium was used to assess GLP-1 levels, whereas the cells were used for protein level analysis.
3T3-L1 cells were cultured in DMEM. Cells were seeded in 6-well plates at a density of 8 × 104 cells/well, and the medium was changed until the wells were fully occupied. For differentiation, cells were cultured in a differentiation medium (0.5 mM IBMX, 0.5 μM dexamethasone, and 10 μg/mL insulin). Subsequently, the medium was changed every 2 d with a maintenance medium containing 10 μg/mL insulin and LCM (0–250 μg/mL) until the 8th day of culture.
4.5. MTT Assay
Cellular toxicity of LCM was assessed using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) solution in both NCI-h716 and 3T3-L1 cells. The cells were seeded in 96-well plates and cultured overnight. Subsequently, the culture medium was replaced with media containing various concentrations of LCM (0, 62.5, 125, and 250 μg/mL). Following incubation under the specified experimental conditions, MTT solution (2 mg/mL) was added to achieve a final concentration of 0.5 mg/mL, and the cells were further incubated for 2 h. Formazan crystals were dissolved in DMSO, and the absorbance was measured at 540 nm using a microplate reader.
4.6. ELISA
For the analysis of GLP-1 and insulin levels, ELISA kits were used following the protocols provided by the respective manufacturers.
4.7. Western Blot
Proteins were extracted from cells using a cell signaling lysis buffer. Protein concentrations were quantified using Bradford dye. Subsequently, each protein sample was separated using SDS-PAGE on gels with varying acrylamide concentrations (10% and 12%) to isolate proteins based on their sizes. The separated proteins were then transferred from the acrylamide gel to a nitrocellulose (NC) membrane. The membranes were blocked with 3% BSA in TBS-T for 1 h. Primary antibodies, diluted at a 1:1000 ratio, were applied for overnight incubation at 4 °C. Afterward, the membrane underwent washing with TBS-T and was subsequently incubated with secondary antibodies, diluted at a 1:10,000 ratio, for 1 h. The bands were visualized with ECL solution using ImageQuantTM LAS500 chemiluminescence (GE Healthcare Bio-Sciences, Uppsala, Sweden) and quantified using ImageJ software
https://imagej.net/ij/ (accessed on 3 August). The primary antibodies used are as follows: C/EBP α, PPAR γ, SREBP 1c, FAS, p-AMPK, AMPK, p-PKAc, PKAc, FABP4, and β-actin.
4.8. Oil Red O Assay
In accordance with the experimental conditions, LCM-treated 3T3-L1 cells were washed with PBS. Cells were fixed by immersion in 10% formalin for 1 h. The cells were washed with 60% isopropanol and allowed to air-dry. A working solution of 60% Oil Red O dissolved in distilled water (DW), was applied to the cells for 30 min. After staining, the cells were rinsed thrice with DW. Images of lipid droplet-stained cells were captured using an Olympus IX71 microscope (Olympus, Tokyo, Japan). To quantify lipid accumulation, the stained cells were dissolved in 100% isopropanol and absorbance was measured at 490 nm using a microplate reader.
4.9. Animals
All animal experiments were conducted with the review and approval of the Institutional Animal Care and Use Committee of Kyung Hee University (approval no. KHSASP-23–308). Five-week-old male C57BL/6J mice were obtained from Daehan BioLink (DBL, Chungcheongbuk-do, Republic of Korea). The animals were provided with access to sterilized mouse chow and water ad libitum. They were acclimated to a controlled environment for one week before the commencement of the experiments. During this period, the mice were maintained in a room with a consistent 12-h light–dark cycle, controlled temperature, and humidity.
4.10. In Vivo Experiments
Following the adaptation period, the mice were fed a high-fat chow diet (D12492, RD 60% fat calories) for 12 weeks, except those in the normal diet (ND) group (N = 5). At week 9, the mice on a high-fat diet had an average body weight of 40 g, and were normalized and divided into two groups (N = 5). Starting from the 9th week of the high-fat chow diet, LCM was orally administered at a dose of 250 mg/kg three times per week, with PBS serving as the vehicle. Throughout the study, all mice underwent regular weight measurements three times a week, and food intake was assessed once a week. An Oral Glucose Tolerance Test (OGTT) was conducted one week before the conclusion of the experiment to evaluate blood glucose levels. On the final day of the experiment, all mice were euthanized and serum, liver tissue, epididymal white adipose tissue (eWAT), and inguinal white adipose tissue (iWAT) were collected. The weight of each tissue sample was recorded for further analysis.
4.11. Serum Analysis
Blood samples were collected in 1.5 mL microtubes pre-coated with EDTA before dissection. Following collection, the samples were centrifuged at 2000 rpm for 10 min at 4 °C to isolate the serum, which was subsequently stored at −80 °C. External laboratory services provided by DKKOREA (Seoul, Republic of Korea) were used to analyze total cholesterol (TC), triglyceride (TG), low-density lipoprotein (LDL), and high-density lipoprotein (HDL) levels. Additionally, GLP-1 and insulin levels were measured using ELISA.
4.12. OGTT
To conduct an Oral Glucose Tolerance Test (OGTT) at a dose of 5 g/kg, mice were subjected to a 16-h fasting period. Glucose (5 g/kg) was administered orally, and blood glucose levels were measured at six different time points via the tail vein. Measurements were performed using the Accu-Chek Performa system (Roche Diagnostics, Mannheim, Germany) at the following time intervals: 0 (prior to oral glucose administration), 15 (15 min after oral glucose administration), and 30, 60, and 120 min. Blood glucose levels were recorded at least twice at each time point to ensure the accuracy and consistency of the data. To evaluate the OGTT, the area under the curve (AUC) was calculated from 0 to 120 min.
4.13. H&E Staining
The collected eWAT, iWAT, and liver tissues were fixed in 10% formalin. After fixation, the tissues were rinsed under running tap water for 24 h and subsequently paraffinized. Paraffin blocks were then prepared by embedding, and 4 μm sections were cut. The sections were deparaffinized in xylene, rehydrated with 100%, 90%, 80%, and 70% ethanol, and washed in PBS. Subsequently, the sections were stained with Harris hematoxylin for 2 min and Eosin Y solution for 30 s. Dehydration was performed using 70%, 80%, 90%, and 100% ethanol. The sections were then cleared in xylene to remove EtOH, and the dehydrated sections were mounted using DPX Mountant (Sigma, St. Louis, MO, USA). Images were captured under an IX71 microscope (Olympus, Tokyo, Japan).
4.14. Statistical Analysis
The significance of each comparison was analyzed by an unpaired t-test (two-tailed) using GraphPad Prism software (Version 5.0; San Diego, CA, USA). All experimental data are expressed as means ± standard deviations.