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DOI: 10.1055/a-1853-7101
Anti-adipogenic Effects of Sulforaphane-rich Ingredient with Broccoli Sprout and Mustard Seed in 3T3-L1 Preadipocytes
Supported by: 2020 Research Grant from Gangneung Science & Industry Promotion Agency Supported by: the BK21 FOUR (Fostering Outstanding Universities for Research) funded by the Ministry of Education (MOE, Korea) and National Research Foundation of Korea (NRF) 4299990913942 Supported by: Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (MOE, Korea) NRF-2017R1D1A3B0602846915 Supported by: Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education NRF-2021R1A6A1A03044242
- Abstract
- Introduction
- Results and Discussion
- Material and Methods
- Contributorsʼ Statement
- References
Abstract
Glucoraphanin (GRA) is a precursor of sulforaphane (SFN), which can be synthesized by the enzyme myrosinase. In this study, we developed and validated HPLC analytical methods for the determination of GRA and SFN in mustard seed powder (MSP), broccoli sprout powder (BSP), and the MSP-BSP mixture powder (MBP), and evaluated their anti-adipogenic effects in 3T3-L1 adipocytes. We found that the analysis methods were suitable for the determination of GRA and SFN in MSP, BSP, and MBP. The content of GRA in BSP was 131.11 ± 1.84 µmol/g, and the content of SFN in MBP was 162.29 ± 1.24 µmol/g. In addition, BSP and MBP effectively decreased lipid accumulation content without any cytotoxicity. Both BSP and MBP significantly inhibited the expression of adipogenic proteins and increased the expression of proteins related to lipolysis and lipid metabolism. BSP and MBP inhibited the expression of adipocyte protein 2 (aP2), CCAAT/enhancer-binding protein-α (C/EBP-α), and peroxisome proliferator-activated receptor-γ (PPAR-γ) in 3T3-L1 adipocytes, and inhibited the expression of fatty acid synthase (FAS) through AMP-activated protein kinase (AMPK). Meanwhile, BSP and MBP also increased the expression of the lipolysis-related proteins, uncoupling protein-1 (UCP-1) and carnitine palmitoyltransferase-1 (CPT-1). Moreover, MBP exerted anti-adipogenic to a greater extent than BSP in 3T3-L1 preadipocytes.
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Key words
Sinapis alba L - Brassica oleracea var. italic - Brassicaceae - Sulforaphane - Analytical method validation - Anti-adipogenicAbbreviations
Introduction
Obesity is a chronic metabolic disease caused by various factors. When energy intake exceeds energy expenditure, excess energy causes mature adipocytes in the body to become hypertrophic and store more fat [1]. When this persistent energy imbalance cannot be reconciled by increasing energy consumption, large adipocytes secrete a series of hormones and cytokines, which promote the differentiation of preadipocytes into mature adipocytes. The number and size of adipocytes increase, causing significant fat deposition, which induces obesity [2]. Obesity is also the main cause of type 2 diabetes, cardiovascular disease, hypertension, arteriosclerosis, and other diseases, and has become a global health problem [3], [4], [5], [6]. Various medicines have been developed to treat obesity and its complications, but many of them, such as sibutramine and orlistat, have disadvantages. Long-term adverse effects include headaches, liver failure, cardiovascular disease, and gastrointestinal diseases [7], [8]. Studies have shown that several plant extracts and bioactive ingredients in plants can effectively regulate fat production, promote lipolysis, and thus play an important role in treating obesity [9], [10], [11].
Sulforaphane (SFN) is a sulfur-rich compound that has many benefits for human health [12], [13], [14]. In vivo and in vitro experimental studies reported that SFN has anti-cancer activity and can reduce the number and size of various types of cancer cells [15], [16]. Experimental evidence in rats suggested that SFN can effectively reduce hypertension and has the potential to prevent heart disease [17]. SFN was reported to improve glucose intolerance in obese mice by upregulating the insulin signaling pathway [18]. Yao et al. proved that SFN induced significant apoptosis and markedly reduced the lipid content in adipocytes [19]. However, the effects of SFN on obesity and its exact mechanism are not yet clear. Chemical synthesis of SFN is costly and time-consuming, requires several highly toxic substances, and the final products from these reactions require further purification. These disadvantages limit the use of synthesized SFN as a food additive [20] and necessitate the development of natural SFNs.
Cruciferous plants are diverse and have a long history of cultivation. Cruciferous vegetables such as radish, cabbage, and broccoli are commonly consumed [21]. Glucoraphanin (GRA) is a glucosinolate that is prominently found in cruciferous vegetables, is the precursor of SFN, and is converted to SFN by the enzyme myrosinase [22], [23]. GRA is less effective in forming SFN through the endogenous route, and it easily forms SFN nitrile due to the effects of temperature, pH, and epithiospecifier protein [24]. Exogenous hydrolysis can be used to avoid the formation of SFN nitrile and obtain more SFN. Previous studies have shown that the GRA content in broccoli and broccoli sprouts is very high [21], [25], [26] and that GRA and myrosinase can be extracted from broccoli sprouts and mustard seeds, respectively [27], [28]. However, reaction conditions during the exogenous hydrolysis process could be better controlled to produce more SFN [24], [29]. Natural SFN can, therefore, be obtained by exogenous reactions of GRA and myrosinase extracted from plants. To date, the anti-adipogenic effects of GRA and SFN have not been fully studied. In this study, we used mustard seed powder (MSP) with a higher myrosinase activity and broccoli sprout powder (BSP) with a high GRA content. The MSP-BSP mixture powder (MBP), with a high SFN content, was obtained through exogenous hydrolysis. We developed and validated analytical methods to determine the GRA and SFN in MSP, BSP, and MBP, and evaluate their anti-adipogenic effects in 3T3-L1 adipocytes. The inhibitory effects and mechanism of inhibition of MSP, BSP, and MBP on lipid accumulation during 3T3-L1 adipocyte differentiation were studied and verified by Oil Red O (ORO) staining and western blot analysis.
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Results and Discussion
The specificity of an HPLC method was determined by its ability to detect the target analyte in the presence of interfering substances [30]. In this study, the specificity of the method was determined by comparing the photodiode array (PDA) spectra and retention times of GRA, SFN standard (STD) and MSP, BSP, and MBP samples. The results are shown in [Fig. 1] and [2]. The peak retention time of GRA standard solution was 4.96 min, the maximum absorption wavelength was 224.3 nm, and the GRA was only detected in BSP samples, with a peak retention time of 5.00 min and a maximum absorption wavelength of 224.3 nm. The peak retention time and PDA spectra of BSP samples were the same as those of GRA STD solution ([Fig. 1]). In this figure the reason for the baseline change after 14 min was due to the gradient which ran from 98% 0.05 M NaH2PO4 to 100% methanol at 224 nm. Because methanol has significantly stronger UV absorbance there than water, the baseline rises, falling at 19 minutes because the gradient runs from 100% methanol to 98% 0.05 M NaH2PO4 at 224 nm ([Fig. 1 a] and Table 1S, Supporting Information). The baseline dropped because of the decrease in absorbance resulting from a decrease in methanol [31]. This, however, does not affect the detection of GRA, which was detected at 5 minutes. De Nicola et al. carried out molar extinction coefficient determination of GRA standard by HPLC analysis method, showing that GRA showed a maximum absorbance at 225 nm [32]; the spectrum obtained was basically similar to this study. The peak retention time of SFN STD solution was 8.18 min, the maximum absorption wavelength was 238.5 nm, and SFN was only detected in MBP samples, with a peak retention time of 8.07 min and maximum absorption wavelength of 238.5 nm. The peak retention time and PDA spectra of MBP samples were the same as those of SFN STD solution ([Fig. 2]).




Linearity, limit of detection (LOD) and limit of quantitation (LOQ)
As shown in [Table 1], the calibration curve was prepared by HPLC analysis with gradually diluted GRA STD solutions from 200 to 25 µg/mL and SFN STD solutions from 177.30 to 2.77 µg/mL. The correlation coefficients (R2) of the calibration curves of GRA and SFN were 0.9999, and the linearity was good. The LOD was 0.85 µg/mL and 0.09 µg/mL, and the LOQ was 2.56 µg/mL and 0.27 µg/mL, respectively.
Analytes |
Range (µg/mL) |
Slope |
Intercept |
Coefficient of determination (R2) |
LOD1 (µg/mL) |
LOQ2 (µg/mL) |
---|---|---|---|---|---|---|
1 LOD is the limit of detection; 2 LOQ is the limit of quantification |
||||||
Glucoraphanin |
25.00 – 200.00 |
1077.55 |
750.53 |
0.9999 |
0.85 |
2.56 |
Sulforaphane |
2.77 – 177.30 |
20 227.09 |
− 28 033.13 |
0.9999 |
0.09 |
0.27 |
Accuracy indicates the degree of agreement in test results generated by the method to the true value, which is also the difference between the measured value and the true value. Accuracy is measured by spiking the sample with a known concentration of analyte standard and analyzing the sample using the “method being validated” [30]. The accuracy was determined by calculating the recovery rate by adding GRA (50, 100, 150 µg/mL) and SFN (22.16, 44.33, 88.65 µg/mL) standard solution concentrations to the samples, respectively. [Tables 2] and [3]) show the intra-day accuracy results of GRA and SFN in MSP as 98.37%~115.34% and 86.73%~90.72%, respectively and the inter-day accuracy results as 94.61%~114.72% and 97.71%~101.90%, respectively. The intra-day accuracy results of GRA and SFN in BSP were 113.04%~119.37% and 91.06%~97.34% and the inter-day accuracy results were 105.41%~107.61% and 94.76%~98.37%, respectively. The intra-day accuracy results of GRA and SFN in MBP were 92.57%~117.78% and 98.86%~103.37% and the inter-day accuracy results were 93.15%~102.69% and 99.63%~100.60%, respectively. The International Conference for Harmonization (ICH) guidelines recommend the use of confidence intervals to report accuracy results and point out that no individual percentage recovery should be less than 80% or greater than 120% [30]. The accuracy of the results of this study was within the specified range. Precision is expressed by relative standard deviation (RSD).
Sample |
Concentration (µg/mL) |
Mean ± SD (µg/mL) |
RSD1 (%) |
Recovery (%) |
|
---|---|---|---|---|---|
1 RSD is the relative standard deviation; 2 MSP: mustard seed powder; 3 BSP: broccoli sprout powder; 4 MBP: MSP-BSP mixture powder |
|||||
MSP2 |
intra-day |
50 |
49.80 ± 0.99 |
1.99 |
99.60 |
100 |
98.37 ± 0.81 |
0.82 |
98.37 |
||
150 |
173.01 ± 0.65 |
0.37 |
115.34 |
||
inter-day |
50 |
48.21 ± 0.50 |
1.03 |
96.42 |
|
100 |
94.61 ± 1.56 |
1.65 |
94.61 |
||
150 |
172.08 ± 1.68 |
0.98 |
114.72 |
||
BSP3 |
intra-day |
50 |
56.79 ± 0.52 |
0.92 |
113.58 |
100 |
113.02 ± 1.85 |
1.63 |
113.04 |
||
150 |
179.06 ± 0.83 |
0.47 |
119.37 |
||
inter-day |
50 |
53.80 ± 0.35 |
0.65 |
107.61 |
|
100 |
105.41 ± 1.71 |
1.62 |
105.41 |
||
150 |
159.55 ± 1.11 |
0.70 |
106.37 |
||
MBP4 |
intra-day |
50 |
58.89 ± 0.52 |
0.88 |
117.78 |
100 |
92.57 ± 0.91 |
0.99 |
92.57 |
||
150 |
155.55 ± 1.87 |
1.20 |
103.70 |
||
inter-day |
50 |
51.06 ± 0.60 |
1.17 |
102.13 |
|
100 |
93.15 ± 0.81 |
0.87 |
93.15 |
||
150 |
154.0 4 ± 1.77 |
1.15 |
102.69 |
Sample |
Concentration (µg/mL) |
Mean ± SD (µg/mL) |
RSD1 (%) |
Recovery (%) |
|
---|---|---|---|---|---|
1 RSD is the relative standard deviation; 2 MSP: mustard seed powder; 3 BSP: broccoli sprout powder; 4 MBP: MSP-BSP mixture powder |
|||||
MSP2 |
intra-day |
22.16 |
21.57 ± 0.41 |
1.88 |
86.73 |
44.33 |
40.36 ± 0.97 |
2.40 |
90.72 |
||
88.65 |
83.18 ± 0.97 |
1.16 |
89.70 |
||
inter-day |
22.16 |
22.58 ± 0.36 |
1.58 |
101.90 |
|
44.33 |
44.06 ± 0.48 |
1.10 |
99.40 |
||
88.65 |
86.62 ± 1.12 |
1.30 |
97.71 |
||
BSP3 |
intra-day |
22.16 |
19.22 ± 0.19 |
0.98 |
97.34 |
44.33 |
40.21 ± 0.17 |
0.42 |
91.06 |
||
88.65 |
79.52 ± 0.99 |
1.24 |
93.83 |
||
inter-day |
22.16 |
21.00 ± 0.18 |
0.88 |
94.76 |
|
44.33 |
43.60 ± 0.98 |
2.25 |
98.37 |
||
88.65 |
86.19 ± 0.05 |
0.05 |
97.22 |
||
MBP4 |
intra-day |
22.16 |
22.91 ± 0.50 |
2.20 |
103.37 |
44.33 |
43.82 ± 1.06 |
2.43 |
98.86 |
||
88.65 |
89.18 ± 0.95 |
1.06 |
100.60 |
||
inter-day |
22.16 |
22.28 ± 0.52 |
2.34 |
100.55 |
|
44.33 |
44.16 ± 0.56 |
1.28 |
99.63 |
||
88.65 |
89.18 ± 1.19 |
1.34 |
100.60 |
As shown in these tables, in the MSP, the intra-day precision results of GRA and SFN were 0.37%~1.99% and 1.16%~2.40% and the inter-day precision results were 0.98%~1.65% and 1.10%~1.58%, respectively. The intra-day precision results of GRA and SFN in BSP were 0.47%~1.63% and 0.42%~1.24%, and the inter-day precision results were 0.65%~1.62% and 0.05%~2.25%, respectively. The intra-day precision results of GRA and SFN in MBP were 0.88%~1.20% and 1.06%~2.43%, and the inter-day precision results were 0.87 – 1.17% and 1.28 – 2.34%, respectively.
The contents of GRA and SFN in MSP, BSP, and MBP were analyzed by HPLC. As shown in [Table 4], GRA and SFN were not detected in the MSP. GRA was detected in BSP at a concentration of 131.11 ± 1.84 µmol/g, and SFN was not detected. SFN was detected in MBP at a concentration of 162.29 ± 1.24 µmol/g, and GRA was not detected. It also indicated that all GRA contained in BSP had been completely hydrolyzed to SFN after the reaction of BSP and MSP in water at 37 °C for 1 hour.
Sample |
Glucoraphanin (µmol/g) |
Sulforaphane (µmol/g) |
---|---|---|
1 ND is the not detected; 2 Results are presented as the mean ± SD of independent experiments in triplicate; 3 MSP: mustard seed powder; 4 BSP: broccoli sprout powder; 5 MBP: MSP-BSP mixture powder |
||
MSP3 |
N. D.1 |
N. D. |
BSP4 |
131.11 ± 1.842 |
N. D. |
MBP5 |
N. D. |
162.29 ± 1.24 |
In our study, MBP was obtained by the reaction of BSP solution and MSP solution in a ratio of 10 : 1 (v/v). Referring to the concentration group experiment performed in adipocytes [33], [34], [35], [36], the following experimental groups were formulated to conduct experiments. The cytotoxicity of SFN (20 µM), MSP (5, 15 µg/mL), BSP (50, 150 µg/mL), and MBP (25, 50, 100 µg/mL) in 3T3-L1 preadipocytes was determined by the 2,3-bis(2-methoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide (XTT) assay. As shown in [Fig. 3 a], 3T3-L1 preadipocytes were treated with SFN 20 µM, MSP (5, 15 µg/mL), BSP (50, 150 µg/mL), and MBP (25, 50, 100 µg/mL) for 8 days. The cell activities were 107.66 ± 1.76%, 102.78 ± 3.25%, 101.54 ± 8.38%, 99.48 ± 4.11%, 99.71 ± 1.71%, 105.61 ± 2.63%, 107.20 ± 3.65%, and 106.72 ± 3.82%, respectively. There were no statistically significant differences between the experimental and control groups (CON). The results showed that SFN (20 µM), MSP (5, 15 µg/mL), BSP (50, 150 µg/mL), and MBP (25, 50, 100 µg/mL) were not toxic to 3T3-L1 preadipocytes. Therefore, the 3T3-L1 preadipocytes were treated with SFN (20 µM), MSP (5, 15 µg/mL), BSP (50, 150 µg/mL), and MBP (25, 50, 100 µg/mL) to further determine the anti-adipogenic effect of each sample and its mechanism.


The effects of MSP (5, 15 µg/mL), BSP (50, 150 µg/mL), and MBP (25, 50, 100 µg/mL) on lipid accumulation during the differentiation of 3T3-L1 adipocytes were evaluated by ORO staining. [Fig. 3 b] shows the results of lipid accumulation in 3T3-L1 preadipocytes after 8 days of treatment with MSP (5, 15 µg/mL), BSP (50, 150 µg/mL), MBP (25, 50, 100 µg/mL), N-acetyl-L-cysteine (NAC) (5 mM); the NAC experimental group was used as a positive control group, which had a significant inhibitory effect on adipogenesis [37], and standard SFN (20 µM). Compared with the CON group, lipid accumulation in 3T3-L1 cells was significantly reduced in the experimental group treated with NAC (5 mM), SFN (20 µM), BSP (50, 150 µg/mL), and MBP (25, 50, 100 µg/mL). In the NAC (5 mM) treatment group, the amount of lipid accumulation in the cells decreased to 26.96 ± 0.55%. In the SFN (20 µM) treatment group, the amount of lipid accumulation in the cells decreased to 26.61 ± 1.25%. In the BSP, at concentrations of 50 and 150 µg/mL, lipid accumulation in cells decreased to 84.87 ± 10.23% and 83.86 ± 9.65%, respectively. In the MBP, at concentrations of 25, 50, and 100 µg/mL, lipid accumulation in cells decreased to 67.64 ± 1.84%, 53.53 ± 3.12% and 26.24 ± 1.58%, respectively. The results showed that NAC (5 mM), SFN (20 µM), BSP (50, 150 µg/mL), and MBP (25, 50, 100 µg/mL) significantly inhibited lipid accumulation in 3T3-L1 cells, and the inhibitory effect of MBP on lipid accumulation was dose-dependent. In the MSP, at concentrations of 5 and 15 µg/mL, the amount of lipid accumulation in the cells was not affected compared with that in the CON group (p > 0.05).
During the differentiation of preadipocytes into mature adipocytes, changes in adipogenesis and cell morphology are caused by the expression of specific adipogenic proteins during the differentiation process [38]. Adipogenic proteins are important regulators of lipid and energy metabolism in the human body [39]. When hormonal induction of differentiation occurs, C/EBP-β and C/EBP-δ are rapidly expressed and drive subsequent expression of C/EBPα and PPARγ [40]. As an adipocyte-specific transcription factor, PPARγ plays a central role in adipocyte gene expression and is involved in the differentiation process [41]. Studies have shown that peroxisome proliferator-activated receptor-γ (PPAR-γ) and CCAAT/enhancer-binding protein-α (C/EBP-α) are key proteins involved in adipogenesis. PPAR-γ can also activate the expression of adipocyte protein 2 (aP2) during adipocyte differentiation [42], [43], [44]. Therefore, inhibition of adipogenesis can be achieved by inhibiting the expression of these adipogenic proteins. To further investigate the inhibitory mechanism of MSP, BSP, and MBP on adipogenesis in 3T3-L1 adipocytes, the adipogenic transcription factors C/EBPα, PPARγ, and aP2 in 3T3-L1 adipocytes were analyzed by western blotting. The results showed that BSP (50, 150 µg/mL) and MBP (25, 50, 100 µg/mL) significantly inhibited the expression of adipogenic proteins C/EBPα, PPARγ, and aP2 compared with the CON group ([Fig. 4]). The protein expression of C/EBPα, PPARγ, and aP2 was dose-dependently decreased by MBP treatment. Compared with the CON group, the expression of adipogenic proteins C/EBPα, PPARγ, and aP2 in 3T3-L1 adipocytes treated with MBP 100 µg/ml decreased to 21.96 ± 3.35%, 28.63 ± 2.84%, and 29.60 ± 1.47%, respectively. There was no significant difference between the MSP (5, 15 µg/mL) treatment groups and the CON group (p > 0.05). The results further showed that BSP and MBP significantly inhibited adipogenesis in 3T3-L1 adipocytes by downregulating the expression of adipogenic proteins C/EBPα, PPARγ, and aP2.


Acetyl-CoA carboxylase (ACC) and fatty acid synthase (FAS) play an important role in the synthesis of triglycerides. ACC converts acetyl-CoA to malonyl-CoA, and FAS catalyzes the formation of palmitic acid by malonyl-CoA and acetyl-CoA, thus regulating fatty acid biosynthesis [45], [46]. To determine whether MSP, BSP, and MBP can inhibit fat synthesis during adipocyte differentiation, the effects of MSP, BSP, and MBP on the expression of FAS and ACC proteins were analyzed. ([Fig. 5 a, b]). This shows the effect on FAS and ACC proteins expression in 3T3-L1 cells treated with MSP (5, 15 µg/mL), BSP (50, 150 µg/mL), and MBP (25, 50, 100 µg/mL). The expression of FAS protein in the BSP and MBP groups was significantly lower than in the CON group (p < 0.05). The inhibition of FAS protein expression in the MBP group was higher than that in the BSP group ([Fig. 5 a]). Both BSP and MBP promoted the expression of the phospho-acetyl-CoA carboxylase (p-ACC-Ser79) protein, compared with the CON group, with the MBP group having a more significant effect on promoting the expression of the p-ACC-Ser79 protein compared with the BSP group ([Fig. 5 b]). There was no significant difference in the expression of FAS and p-ACC-Ser79 proteins in the MSP group compared with the CON group. These results indicate that both BSP and MBP can effectively reduce lipid accumulation by inhibiting fat synthesis and promoting fatty acid metabolism. The anti-adipogenic effect of MBP was excellent.


AMP-activated protein kinase (AMPK), as a cellular energy sensor, can sense changes in the AMP/ATP ratio. The increased AMP/ATP ratio stimulates the activation of AMPK, and the increased phosphorylation of AMPK promotes the expression of carnitine palmitoyltransferase-1 (CPT-1) and uncoupling protein-1 (UCP-1), thus increasing the oxidative metabolism of fatty acids and promoting lipid consumption [47], [48]. To comprehensively characterize the metabolic effects of MSP, BSP, and MBP in 3T3-L1 adipocytes, the expression of proteins related to lipid metabolism was studied. As shown in [Fig. 6], the expression levels of CPT-1, UCP-1, and AMPK phosphorylated proteins were increased in the experimental group treated with BSP and MBP compared with the CON group. The CPT-1, UCP-1, and AMPK phosphorylated proteins significantly increased (p < 0.05) in the MBP experimental group compared with the BSP experimental group. There were no significant differences in the expression levels of all proteins between the MSP and CON groups. The results indicate that BSP and MBP can promote lipid metabolism by activating the AMPK signaling pathway and increasing the expression of CPT-1 and UCP-1 proteins. Both BSP and MBP have excellent anti-adipogenic effects, with MBP having the more pronounced effect. BSP and MBP treatment suppressed the adipocytes differentiation, and significantly decreased lipogenesis-related proteins (PPAR-γ, C/EBPα-, aP2, FAS), as well as fatty acid oxidation proteins (CPT-1 and UCP-1) expression. The anti-adipogenic properties showed by BSP and MBP possibly involved the underlying mechanism mediated by activation of the AMPK pathway. In general, BSP and MBP have great promise for the prevention and treatment of obesity, especially MBP.


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Material and Methods
Chemicals and standards
The chemical standard STD GRA (purity: 99.81%) was obtained from MedChemExpress, and chemical STD SFN (purity ≥ 90%) was purchased from Sigma-Aldrich. HPLC grade methanol and ACN were acquired from J. T. Baker. PBS, FBS, bovine serum (BS), DMEM, penicillin-streptomycin (P/S), and EDTA were obtained from Gibco. Insulin, 3-isobutyl-1-methylxanthine (IBMX), NAC, ORO, dexamethasone (DEX), and sodium phosphate monobasic (NaH2PO4) were supplied by Sigma-Aldrich.
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Preparation of samples
In this study, MSP, BSP, and MBP were obtained from the Research and Development Center, Milae Bioresources Co. Ltd., Seoul, Korea. Mustard seed and broccoli sprout were identified by Dr. Jong-Kwon Han, Research and Development Center, Milae Bioresources Co., Ltd. (Seoul, Korea). Experimental samples were obtained using the following treatment methods. An experimental sample of MSP was prepared by adding MSP (150 mg) to 10 mL of deionized water and stirring thoroughly. Next, the sample sonicated for 30 min in an ultrasonic cleaning bath (JAC 4020 type, 60 Hz, 620 W, Ultrasonic) and was filtered with a 0.45 µm pore size poly tetra fluoroethylene syringe filter (Teknokroma). The BSP was prepared by treatment in an autoclave to inactivate the enzymes and then by adding a 1.5 g sample to 10 mL deionized water, followed by the method used to treat the MSP. To prepare the MBP experimental sample, 100 mg MSP was mixed in the 1 mL deionized water and stirred for 15 minutes. BSP was autoclaved to inactivate the enzyme, then 100 mg BSP was mixed in the 1 mL deionized water and stirred for 15 minutes. Finally, the MSP mixture and BSP mixture were mixed in a volume ratio of 1 : 10 (v/v), and then reacted in 37 °C water for one hour. The final solution was freeze-drying to obtain a powder sample (MBP), which was dissolved in dimethyl sulfoxide (99% purity) to obtain the MBP experimental sample with a concentration range of 25 – 100 mg/mL, and further 1000× diluted in the adequate culture medium (0.1% (v/v) final dimethyl sulfoxide concentration).
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HPLC instrument conditions
The samples were analyzed by HPLC (2695 separation module; Waters) equipped with a 996 PDA detector and a Shiseido Capcell Pak C18 UG120 column (4.6 × 250 mm, 5.0 µm). For GRA, the mobile phase comprised methanol/0.05 M NaH2PO4 in water in gradient mode as follows: methanol/water with 0.05 M NaH2PO4 (0 – 10 min, 2 : 98 – 2 : 98 v/v; 10 – 16 min, ~ 100 : 0 v/v; 16 – 19 min, ~ 100 : 0 v/v; 19 – 25 min, ~ 2 : 98 v/v; and 25 – 29 min, ~ 2 : 98 v/v). The running time was 29 min. The flow rate was 1.0 mL/min, and the detection wavelength of the PDA detector was set to 234 nm. The column temperature was maintained at 30 °C, and the injection volume was 10 µL (Table 1S, Supporting Information). For SFN, the mobile phase comprised ACN/double deionized water in gradient mode as follows: ACN/double deionized water (0 – 10 min, 30 : 70 – 35 : 65 v/v; 10 – 14 min, ~ 80 : 20 v/v; 14 – 17 min, ~ 80 : 20 v/v; 17 – 21 min, ~ 30 : 70 v/v; and 21 – 26 min, ~ 30 : 70 v/v). The running time was 26 min. The flow rate was 0.6 mL/min, and the detection wavelength of the PDA detector was set to 202 nm. The column temperature was maintained at 30 °C, and the injection volume was 10 µL (Table 2S, Supporting Information).
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Method validation
The HPLC method for the determination of GRA and SFN in MSP, BSP, and MBP was verified using the specificity, linearity, precision, accuracy, LOD, and LOQ based on the guidelines of the International Conference for Harmonization (ICH) [30]. The STD GRA and SFN were used to prepare seven concentration increments ranging from 25 to 200 µg/mL and 2.77 to 177.30 µg/mL, respectively. The linearity was evaluated using a calibration curve. The LOD and LOQ for the GRA and SFN analytes in the MSP, BSP, and MBP were calculated using a calibration curve and the slope, and then confirmed using the following equation: LOD = (3.3σ)/S, LOQ = (10σ)/S (S: slope of the calibration curve, σ: standard deviation of the response). Specificity was evaluated by confirming that some ingredients in MSP, BSP, and MBP did not interfere with the target analytes. The precision and accuracy of the two matrices were determined at three different concentrations (GRA: 50, 100, and 150 µg/mL; SFN: 22.16, 44.33, and 88.65 µg/mL). The results were appraised by intra-day (three times on the same day) and inter-day (three times on three different days) measurements.
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Cell culture and differentiation
The 3T3-L1 preadipocytes were purchased from the American Type Culture Collection and seeded into 100, 96, and 24-well plates at a density of 5 × 106 cells/well in DMEM containing 10% BS, 3.7 g/L sodium bicarbonate, and 1% P/S at 37 °C in 5% CO2 until the cells reached 100% confluence. After two days, the DMEM containing adipocyte differentiation-inducing substances with 0.5 mM IBMX, 1 µM DEX, 1 µg/mL insulin (MDI), 10% P/S, and 10% FBS were used to induce the differentiation of preadipocytes into adipocytes. At the time of adipocyte differentiation (day 0), the concentration of the SFN sample was 20 µM, the MSP sample was 5, 15 µg/mL, the BSP sample was 50, 150 µg/mL, and the MBP samples were 25, 50, and 100 µg/mL. The cells were treated with 5 mM NAC as a positive control group. After two days, the medium was replaced with fresh medium containing only 1 µg/mL insulin and 10% FBS and subsequently changed every two days until the eighth day of differentiation.
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Cell viability assay
Cell viability was assessed using the XTT assay (WelGene). The cells were seeded on a 96-well plate at 1 × 105 cells/well and differentiated with an induction medium containing MSP, BSP, and MBP for 8 days. XTT and N-methyl dibenzopyrazine methyl sulfate (PMS) were mixed at a ratio of 50 : 1 (v/v), added to each well, and then incubated at 37 °C for four hours. The absorbance was measured at 450 nm (with 690 nm as the reference wavelength) using a microplate reader (SpectraMax i3; Molecular Devices), and the cell viability was calculated using the following equation:
Cell viability (%) = (A sample 450 nm − A sample 690 nm)/(A blank 450 nm − A blank 690 nm) × 100
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Oil red O staining assay
After 8 days of induction of 3T3-L1 preadipocyte differentiation, the culture medium was aspirated. The cells were washed twice with PBS and fixed with 10% formaldehyde at room temperature for 1 h. The cells were then washed with 60% isopropanol and completely dried at room temperature. ORO was used to stain the triglycerides in the adipocytes red, and thus determine the accumulation of triglycerides in the adipocytes. The dried cells were stained with ORO solution for 1 h, washed three times with deionized water, and the completely dried again. The red-stained lipid droplets were eluted with 100% isopropanol, and absorbance was measured at 490 nm.
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Western blot analysis
After NAC (5 mM), SFN (20 µM), MSP (5, 15 µg/mL), BSP (50, 150 µg/mL), and MBP (25, 50, 100 µg/mL) treatment, the 3T3-L1 cells were lysed using a protein lysis buffer (50 mM Tris-HCl, 150 mM sodium chloride, 1% Nonidet P-40, 0.1% sodium dodecyl sulfate, 0.25% sodium deoxycholate), and the lysates were centrifuged at 12 000×g for 15 min at 4 °C. After centrifugation, the supernatant was collected, and protein concentrations were determined using a Bio-Rad protein assay kit. The proteins were subjected to 10% SDS-PAGE and transferred to a polyvinylidene difluoride membrane at 100 V for 90 min. The membrane was blocked using 5% skim milk in 1 × Tris-buffered saline containing Tween-20 (TBST) for 1 h at room temperature. After blocking, the membranes were washed three times for 10 min with 1 × TBST and incubated with primary antibodies [β-actin, PPAR-γ, C/EBP-α, aP2, ACC, p-ACC-Ser79, FAS, CPT-1, UCP-1, AMPK, and p-AMPK-Thr172 (Cell Signaling Technology) (1 : 1000)] at 4 °C overnight and then washed three more times with 1 × TBST. The secondary antibody [anti-mouse or anti-rabbit, (Cell Signaling Technology) (1 : 2000)] was incubated for 1 h at room temperature and washed three times with 1×TBST. The target protein bands were detected using enhanced chemiluminescence (BIONOTE) and the images of target protein bands were detected using ChemiDoc image software 5.2.1 (Bio-Rad Laboratories, Inc.).
#
Statistical analysis
Each experiment was repeated three times, and the results were expressed as the mean and standard deviation (SD). Each test group was statistically analyzed by one-way analysis of variance and Duncanʼs multiple test using SPSS software (version 24.0; SPSS Inc), and a value of p < 0.05, which was considered statistically significant.
#
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Contributorsʼ Statement
Conception and design of the work: O. H. Lee, X. Men, S. I. Choi, S. J. Lee, K. T. Park, J. K. Han; data collection: X. Men, S. I. Choi, X. Han, S. J. Lee, K. T. Park, J. K. Han; analysis and interpretation of the data: O. H. Lee, X. Han, S. J. Lee; statistical analysis: X. Men, X. Han, S. J. Lee, K. T. Park, J. K. Han; drafting the manuscript: O. H. Lee, X. Men, S. I. Choi, X. Han, J. K. Han; critical revision of the manuscript: O. H. Lee, S. I. Choi, K. T. Park. The manuscript has been read and approved by all authors.
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#
Conflict of Interest
The authors declare that they have no conflict of interest.
Acknowledgements
This work was supported by the 2020 Research Grant from Gangneung Science & Industry Promotion Agency, the Basic Science Research Program (NRF-2021R1A6A1A03044242) through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, the BK21 FOUR (Fostering Outstanding Universities for Research) (4 299 990 913 942) funded by the Ministry of Education (MOE, Korea) and National Research Foundation of Korea (NRF), and the Basic Science Research Program (NRF-2017R1D1A3B0602846915) through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (MOE, Korea).
* Co-correspondence authors.
Supporting Information
- Supporting Information
The contents of GRA and SFN in MSP, BSP, and MBP were analyzed by HPLC, which was available in the Supporting Information.
-
References
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- 2 Haczeyni F, Bell-Anderson KS, Farrell GC. Causes and mechanisms of adipocyte enlargement and adipose expansion. Obes Rev 2018; 19: 406-420
- 3 Fabbrini E, Sullivan S, Klein S. Obesity and nonalcoholic fatty liver disease: Biochemical, metabolic, and clinical implications. Hepatology 2010; 51: 679-689
- 4 Chen X, Gui G, Ji W, Xue Q, Wang C, Li H. The relationship between obesity subtypes based on BMI and cardio-cerebrovascular disease. Hypertens Res 2019; 42: 912-919
- 5 Leggio M, Lombardi M, Caldarone E, Severi P, DʼEmidio S, Armeni M, Bravi V, Bendini MG, Mazza A. The relationship between obesity and hypertension: An updated comprehensive overview on vicious twins. Hypertens Res 2017; 40: 947-963
- 6 Zhang X, Zhang Y, Wang P, Zhang SY, Dong Y, Zeng G, Yan Y, Sun L, Wu Q, Liu H, Liu B, Kong W, Wang X, Jiang C. Adipocyte hypoxia-inducible factor 2α suppresses atherosclerosis by promoting adipose ceramide catabolism. Cell Metab 2019; 30: 937-951
- 7 Abraham B, Sellin JH. Drug-induced diarrhea. Curr Gastroenterol Rep 2007; 9: 365-372
- 8 Filippatos TD, Derdemezis C, Gazi IF, Nakou ES, Mikhailidis DP, Elisaf MS. Orlistat-associated adverse effects and drug interactions. Drug Saf 2008; 31: 53-65
- 9 Wang HN, Xiang JZ, Qi Z, Du M. Plant extracts in prevention of obesity. Crit Rev Food Sci Nut 2022; 62: 1-14
- 10 de Freitas Junior LM, de Almeida jr. EB. Medicinal plants for the treatment of obesity: Ethnopharmacological approach and chemical and biological studies. Am J Transl Res 2017; 9: 2050-2064
- 11 Veiga M, Costa EM, Sliva S, Pintado M. Impact of plant extracts upon human health: A review. Crit Rev Food Sci Nutr 2020; 60: 873-886
- 12 Kim JK, Park SU. Current potential health benefits of sulforaphane. EXCLI J 2016; 15: 571-577
- 13 Greaney AJ, Maier NK, Leppla SH, Moayeri M. Sulforaphane inhibits multiple inflammasomes through an Nrf2-independent mechanism. J Leukoc Biol 2016; 99: 189-199
- 14 Sikdar S, Papadopoulou M, Dubois J. What do we know about sulforaphane protection against photoaging?. J Cosmet Dermatol 2016; 15: 72-77
- 15 Clarke JD, Dashwood RH, Ho E. Multi-targeted prevention of cancer by sulforaphane. Cancer Lett 2008; 269: 291-304
- 16 Li Y, Zhang T, Korkaya H, Liu S, Lee HF, Newman B, Yu Y, Clouthier SG, Schwartz SJ, Wicha MS, Sun D. Sulforaphane, a dietary component of broccoli/broccoli sprouts, inhibits breast cancer stem cells. Clin Cancer Res 2010; 16: 2580-2590
- 17 Senanayake GVK, Banigesh A, Wu L, Lee P, Juurlink BHJ. The dietary phase 2 protein inducer sulforaphane can normalize the kidney epigenome and improve blood pressure in hypertensive rats. Am J Hypertens 2012; 25: 229-235
- 18 Xu Y, Fu JF, Chen JH, Zhang ZW, Zou ZQ, Han LY, Hua QH, Zhao JS, Zhang XH, Shan YJ. Sulforaphane ameliorates glucose intolerance in obese mice via the upregulation of the insulin signaling pathway. Food Funct 2018; 9: 4695-4701
- 19 Yao A, Shen Y, Wang A, Chen S, Zhang H, Chen F, Chen Z, Wei H, Zou Z, Shan Y, Zhang X. Sulforaphane induces apoptosis in adipocytes via Akt/p70s6k1/Bad inhibition and ERK activation. Biochem Biophys Res Commun 2015; 465: 696-770
- 20 Azizi SN, Amiri-Besheli B, Sharifi-Mehr S. The isolation and determination of sulforaphane from broccoli tissues by reverse phase-High Performance Liquid Chromatography. J Chin Chem Soc 2011; 58: 906-910
- 21 Manchali S, Chidambara Murthy KN, Patil BS. Crucial facts about health benefits of popular cruciferous vegetables. J Funct Foods 2012; 4: 94-106
- 22 Houghton CA, Fassett RG, Coombes JS. Sulforaphane and other nutrigenomic Nrf2 activators: Can the clinicianʼs expectation be matched by the reality?. Oxid Med Cell Longev 2016; 2016: 7857186
- 23 Ghawi SK, Methven L, Niranjan K. The potential to intensify sulforaphane formation in cooked broccoli (Brassica oleracea var. italica) using mustard seeds (Sinapis alba). Food Chem 2013; 138: 1734-1741
- 24 Hanschen FS, Klopsch R, Oliviero T, Schreiner M, Verkerk R, Dekker M. Optimizing isothiocyanate formation during enzymatic glucosinolate breakdown by adjusting pH value, temperature and dilution in Brassica vegetables and Arabidopsis thaliana. Sci Rep 2017; 7: 1-15
- 25 Yagishita Y, Fahey JW, Dinkova-Kostova AT, Kensler TW. Broccoli or sulforaphane: Is it the source or dose that matters?. Molecules 2019; 24: 3593
- 26 Cieślik E, Leszczyńska T, Filipiak-Florkiewicz A, Sikora E, Pisulewski PM. Effects of some technological processes on glucosinolate contents in cruciferous vegetables. Food Chem 2007; 105: 976-981
- 27 Gu Y, Guo Q, Zhang L, Chen Z, Han Y, Gu Z. Physiological and biochemical metabolism of germinating broccoli seeds and sprouts. J Agric Food Chem 2012; 60: 209-213
- 28 Piekarska A, Kusznierewicz B, Meller M, Dziedziul K, Namieśnik J, Bartoszek A. Myrosinase activity in different plant samples; optimisation of measurement conditions for spectrophotometric and pH-stat methods. Ind Crops Prod 2013; 50: 58-67
- 29 Shen L, Su G, Wang X, Du Q, Wang K. Endogenous and exogenous enzymolysis of vegetable-sourced glucosinolates and influencing factors. Food Chem 2010; 119: 987-994
- 30 Walfish S. Analytical methods: A statistical perspective on the ICH Q2A and Q2B guidelines for validation of analytical methods. BioPharm Int 2006; 19: 1-6
- 31 Dolan JW. Gradient elution, Part V: Baseline drift problems. Can anything be done to correct for baseline drift in gradient separations?. LCGC North America 2013; 31: 538-542
- 32 De Nicola GR, Rollin P, Mazzon E, Iori R. Novel gram-scale production of enantiopure R-sulforaphane from Tuscan black kale seeds. Molecules 2014; 19: 6975-6986
- 33 Choi KM, Lee YS, Sin DM, Lee S, Lee MK, Lee YM, Hong JT, Yun YP, Yoo HS. Sulforaphane inhibits mitotic clonal expansion during adipogenesis through cell cycle arrest. Obesity (Silver Spring) 2012; 20: 1365-1371
- 34 Kim GH, Ju JY, Chung KS, Cheon SY, Gil TY, Cominguez DC, Cha YY, Lee JH, Roh SS, An HJ. Rice hull extract (RHE) suppresses adiposity in high-fat diet-induced obese mice and inhibits differentiation of 3T3-L1 preadipocytes. Nutrients 2019; 11: 1162
- 35 Lee MS, Kim Y. Mulberry fruit extract ameliorates adipogenesis via increasing AMPK activity and downregulating microRNA-21/143 in 3T3-L1 adipocytes. J Med Food 2020; 23: 266-272
- 36 Park HJ, Cho JY, Kim MK, Koh PO, Cho KW, Kim CH, Lee KS, Chung BY, Kim GS, Cho JH. Anti-obesity effect of Schisandra chinensis in 3T3-L1 cells and high fat diet-induced obese rats. Food Chem 2012; 134: 227-234
- 37 Calzadilla P, Sapochnik D, Cosentino S, Diz V, Dicelio L, Calvo JC, Guerra LN. N-acetylcysteine reduces markers of differentiation in 3T3-L1 adipocytes. Int J Mol Sci 2011; 12: 6936-6951
- 38 Moseti D, Regassa A, Kim WK. Molecular regulation of adipogenesis and potential anti-adipogenic bioactive molecules. Int J Mol Sci 2016; 17: 124
- 39 Lee HG, Lu YA, Li X, Hyun JM, Kim HS, Lee JJ, Kim TH, Kim HM, Kang MC, Jeon AY. Anti-Obesity effects of Grateloupia elliptica, a red seaweed, in mice with high-fat diet-induced obesity via suppression of adipogenic factors in white adipose tissue and increased thermogenic factors in brown adipose tissue. Nutrients 2020; 12: 308
- 40 Lefterova MI, Zhang Y, Steger DJ, Schupp M, Schug J, Cristancho A, Feng D, Zhuo D, Stoeckert jr. CJ, Liu XS, Lazar MA. PPARγ and C/EBP factors orchestrate adipocyte biology via adjacent binding on a genome-wide scale. Genes Dev 2008; 22: 2941-2952
- 41 Farmer SR. Regulation of PPARγ activity during adipogenesis. Int J Obes (Lond) 2005; 29: 13-16
- 42 Jemai R, Drira R, Makni M, Fetoui H, Sakamoto K. Colocynth (Citrullus colocynthis) seed extracts attenuate adipogenesis by down-regulating PPARγ/SREBP-1c and C/EBPα in 3T3-L1 cells. Food Biosci 2020; 33: 100491
- 43 An Y, Zhang Y, Li C, Qian Q, He W, Wang T. Inhibitory effects of flavonoids from Abelmoschus manihot flowers on triglyceride accumulation in 3T3-L1 adipocytes. Fitoterapia 2011; 82: 595-600
- 44 Tontonoz P, Hu E, Graves RA, Budavari AI, Spiegelman BM. mPPAR gamma 2: Tissue-specific regulator of an adipocyte enhancer. Genes Dev 1994; 8: 1224-1234
- 45 Choi YE, Choi SI, Han X, Men X, Jang GW, Kwon HY, Kang SR, Han JS, Lee OH. Radical scavenging-linked anti-adipogenic activity of Aster Scaber ethanolic extract and its bioactive compound. Antioxidants (Basel) 2020; 9: 1290
- 46 Kawano Y, Cohen DE. Mechanisms of hepatic triglyceride accumulation in non-alcoholic fatty liver disease. J Gastroenterol 2013; 48: 434-441
- 47 Kim N, Nam M, Kang MS, Lee JO, Lee YW, Hwang GS, Kim HS. Piperine regulates UCP1 through the AMPK pathway by generating intracellular lactate production in muscle cells. Sci Rep 2017; 7: 1-13
- 48 Hwang JT, Kim SH, Lee MS, Kim SH, Yang HJ, Kim MJ, Kim HS, Ha J, Kim MS, Kwon DY. Anti-obesity effects of ginsenoside Rh2 are associated with the activation of AMPK signaling pathway in 3T3-L1 adipocyte. Biochem Biophys Res Commun 2007; 364: 1002-1008
Correspondence
Publication History
Received: 13 January 2022
Accepted after revision: 16 May 2022
Accepted Manuscript online:
16 May 2022
Article published online:
11 October 2022
© 2022. Thieme. All rights reserved.
Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany
-
References
- 1 Chait A, den Hartigh LJ. Adipose tissue distribution, inflammation, and its metabolic consequences, including diabetes and cardiovascular disease. Front Cardiovasc Med 2020; 7: 22
- 2 Haczeyni F, Bell-Anderson KS, Farrell GC. Causes and mechanisms of adipocyte enlargement and adipose expansion. Obes Rev 2018; 19: 406-420
- 3 Fabbrini E, Sullivan S, Klein S. Obesity and nonalcoholic fatty liver disease: Biochemical, metabolic, and clinical implications. Hepatology 2010; 51: 679-689
- 4 Chen X, Gui G, Ji W, Xue Q, Wang C, Li H. The relationship between obesity subtypes based on BMI and cardio-cerebrovascular disease. Hypertens Res 2019; 42: 912-919
- 5 Leggio M, Lombardi M, Caldarone E, Severi P, DʼEmidio S, Armeni M, Bravi V, Bendini MG, Mazza A. The relationship between obesity and hypertension: An updated comprehensive overview on vicious twins. Hypertens Res 2017; 40: 947-963
- 6 Zhang X, Zhang Y, Wang P, Zhang SY, Dong Y, Zeng G, Yan Y, Sun L, Wu Q, Liu H, Liu B, Kong W, Wang X, Jiang C. Adipocyte hypoxia-inducible factor 2α suppresses atherosclerosis by promoting adipose ceramide catabolism. Cell Metab 2019; 30: 937-951
- 7 Abraham B, Sellin JH. Drug-induced diarrhea. Curr Gastroenterol Rep 2007; 9: 365-372
- 8 Filippatos TD, Derdemezis C, Gazi IF, Nakou ES, Mikhailidis DP, Elisaf MS. Orlistat-associated adverse effects and drug interactions. Drug Saf 2008; 31: 53-65
- 9 Wang HN, Xiang JZ, Qi Z, Du M. Plant extracts in prevention of obesity. Crit Rev Food Sci Nut 2022; 62: 1-14
- 10 de Freitas Junior LM, de Almeida jr. EB. Medicinal plants for the treatment of obesity: Ethnopharmacological approach and chemical and biological studies. Am J Transl Res 2017; 9: 2050-2064
- 11 Veiga M, Costa EM, Sliva S, Pintado M. Impact of plant extracts upon human health: A review. Crit Rev Food Sci Nutr 2020; 60: 873-886
- 12 Kim JK, Park SU. Current potential health benefits of sulforaphane. EXCLI J 2016; 15: 571-577
- 13 Greaney AJ, Maier NK, Leppla SH, Moayeri M. Sulforaphane inhibits multiple inflammasomes through an Nrf2-independent mechanism. J Leukoc Biol 2016; 99: 189-199
- 14 Sikdar S, Papadopoulou M, Dubois J. What do we know about sulforaphane protection against photoaging?. J Cosmet Dermatol 2016; 15: 72-77
- 15 Clarke JD, Dashwood RH, Ho E. Multi-targeted prevention of cancer by sulforaphane. Cancer Lett 2008; 269: 291-304
- 16 Li Y, Zhang T, Korkaya H, Liu S, Lee HF, Newman B, Yu Y, Clouthier SG, Schwartz SJ, Wicha MS, Sun D. Sulforaphane, a dietary component of broccoli/broccoli sprouts, inhibits breast cancer stem cells. Clin Cancer Res 2010; 16: 2580-2590
- 17 Senanayake GVK, Banigesh A, Wu L, Lee P, Juurlink BHJ. The dietary phase 2 protein inducer sulforaphane can normalize the kidney epigenome and improve blood pressure in hypertensive rats. Am J Hypertens 2012; 25: 229-235
- 18 Xu Y, Fu JF, Chen JH, Zhang ZW, Zou ZQ, Han LY, Hua QH, Zhao JS, Zhang XH, Shan YJ. Sulforaphane ameliorates glucose intolerance in obese mice via the upregulation of the insulin signaling pathway. Food Funct 2018; 9: 4695-4701
- 19 Yao A, Shen Y, Wang A, Chen S, Zhang H, Chen F, Chen Z, Wei H, Zou Z, Shan Y, Zhang X. Sulforaphane induces apoptosis in adipocytes via Akt/p70s6k1/Bad inhibition and ERK activation. Biochem Biophys Res Commun 2015; 465: 696-770
- 20 Azizi SN, Amiri-Besheli B, Sharifi-Mehr S. The isolation and determination of sulforaphane from broccoli tissues by reverse phase-High Performance Liquid Chromatography. J Chin Chem Soc 2011; 58: 906-910
- 21 Manchali S, Chidambara Murthy KN, Patil BS. Crucial facts about health benefits of popular cruciferous vegetables. J Funct Foods 2012; 4: 94-106
- 22 Houghton CA, Fassett RG, Coombes JS. Sulforaphane and other nutrigenomic Nrf2 activators: Can the clinicianʼs expectation be matched by the reality?. Oxid Med Cell Longev 2016; 2016: 7857186
- 23 Ghawi SK, Methven L, Niranjan K. The potential to intensify sulforaphane formation in cooked broccoli (Brassica oleracea var. italica) using mustard seeds (Sinapis alba). Food Chem 2013; 138: 1734-1741
- 24 Hanschen FS, Klopsch R, Oliviero T, Schreiner M, Verkerk R, Dekker M. Optimizing isothiocyanate formation during enzymatic glucosinolate breakdown by adjusting pH value, temperature and dilution in Brassica vegetables and Arabidopsis thaliana. Sci Rep 2017; 7: 1-15
- 25 Yagishita Y, Fahey JW, Dinkova-Kostova AT, Kensler TW. Broccoli or sulforaphane: Is it the source or dose that matters?. Molecules 2019; 24: 3593
- 26 Cieślik E, Leszczyńska T, Filipiak-Florkiewicz A, Sikora E, Pisulewski PM. Effects of some technological processes on glucosinolate contents in cruciferous vegetables. Food Chem 2007; 105: 976-981
- 27 Gu Y, Guo Q, Zhang L, Chen Z, Han Y, Gu Z. Physiological and biochemical metabolism of germinating broccoli seeds and sprouts. J Agric Food Chem 2012; 60: 209-213
- 28 Piekarska A, Kusznierewicz B, Meller M, Dziedziul K, Namieśnik J, Bartoszek A. Myrosinase activity in different plant samples; optimisation of measurement conditions for spectrophotometric and pH-stat methods. Ind Crops Prod 2013; 50: 58-67
- 29 Shen L, Su G, Wang X, Du Q, Wang K. Endogenous and exogenous enzymolysis of vegetable-sourced glucosinolates and influencing factors. Food Chem 2010; 119: 987-994
- 30 Walfish S. Analytical methods: A statistical perspective on the ICH Q2A and Q2B guidelines for validation of analytical methods. BioPharm Int 2006; 19: 1-6
- 31 Dolan JW. Gradient elution, Part V: Baseline drift problems. Can anything be done to correct for baseline drift in gradient separations?. LCGC North America 2013; 31: 538-542
- 32 De Nicola GR, Rollin P, Mazzon E, Iori R. Novel gram-scale production of enantiopure R-sulforaphane from Tuscan black kale seeds. Molecules 2014; 19: 6975-6986
- 33 Choi KM, Lee YS, Sin DM, Lee S, Lee MK, Lee YM, Hong JT, Yun YP, Yoo HS. Sulforaphane inhibits mitotic clonal expansion during adipogenesis through cell cycle arrest. Obesity (Silver Spring) 2012; 20: 1365-1371
- 34 Kim GH, Ju JY, Chung KS, Cheon SY, Gil TY, Cominguez DC, Cha YY, Lee JH, Roh SS, An HJ. Rice hull extract (RHE) suppresses adiposity in high-fat diet-induced obese mice and inhibits differentiation of 3T3-L1 preadipocytes. Nutrients 2019; 11: 1162
- 35 Lee MS, Kim Y. Mulberry fruit extract ameliorates adipogenesis via increasing AMPK activity and downregulating microRNA-21/143 in 3T3-L1 adipocytes. J Med Food 2020; 23: 266-272
- 36 Park HJ, Cho JY, Kim MK, Koh PO, Cho KW, Kim CH, Lee KS, Chung BY, Kim GS, Cho JH. Anti-obesity effect of Schisandra chinensis in 3T3-L1 cells and high fat diet-induced obese rats. Food Chem 2012; 134: 227-234
- 37 Calzadilla P, Sapochnik D, Cosentino S, Diz V, Dicelio L, Calvo JC, Guerra LN. N-acetylcysteine reduces markers of differentiation in 3T3-L1 adipocytes. Int J Mol Sci 2011; 12: 6936-6951
- 38 Moseti D, Regassa A, Kim WK. Molecular regulation of adipogenesis and potential anti-adipogenic bioactive molecules. Int J Mol Sci 2016; 17: 124
- 39 Lee HG, Lu YA, Li X, Hyun JM, Kim HS, Lee JJ, Kim TH, Kim HM, Kang MC, Jeon AY. Anti-Obesity effects of Grateloupia elliptica, a red seaweed, in mice with high-fat diet-induced obesity via suppression of adipogenic factors in white adipose tissue and increased thermogenic factors in brown adipose tissue. Nutrients 2020; 12: 308
- 40 Lefterova MI, Zhang Y, Steger DJ, Schupp M, Schug J, Cristancho A, Feng D, Zhuo D, Stoeckert jr. CJ, Liu XS, Lazar MA. PPARγ and C/EBP factors orchestrate adipocyte biology via adjacent binding on a genome-wide scale. Genes Dev 2008; 22: 2941-2952
- 41 Farmer SR. Regulation of PPARγ activity during adipogenesis. Int J Obes (Lond) 2005; 29: 13-16
- 42 Jemai R, Drira R, Makni M, Fetoui H, Sakamoto K. Colocynth (Citrullus colocynthis) seed extracts attenuate adipogenesis by down-regulating PPARγ/SREBP-1c and C/EBPα in 3T3-L1 cells. Food Biosci 2020; 33: 100491
- 43 An Y, Zhang Y, Li C, Qian Q, He W, Wang T. Inhibitory effects of flavonoids from Abelmoschus manihot flowers on triglyceride accumulation in 3T3-L1 adipocytes. Fitoterapia 2011; 82: 595-600
- 44 Tontonoz P, Hu E, Graves RA, Budavari AI, Spiegelman BM. mPPAR gamma 2: Tissue-specific regulator of an adipocyte enhancer. Genes Dev 1994; 8: 1224-1234
- 45 Choi YE, Choi SI, Han X, Men X, Jang GW, Kwon HY, Kang SR, Han JS, Lee OH. Radical scavenging-linked anti-adipogenic activity of Aster Scaber ethanolic extract and its bioactive compound. Antioxidants (Basel) 2020; 9: 1290
- 46 Kawano Y, Cohen DE. Mechanisms of hepatic triglyceride accumulation in non-alcoholic fatty liver disease. J Gastroenterol 2013; 48: 434-441
- 47 Kim N, Nam M, Kang MS, Lee JO, Lee YW, Hwang GS, Kim HS. Piperine regulates UCP1 through the AMPK pathway by generating intracellular lactate production in muscle cells. Sci Rep 2017; 7: 1-13
- 48 Hwang JT, Kim SH, Lee MS, Kim SH, Yang HJ, Kim MJ, Kim HS, Ha J, Kim MS, Kwon DY. Anti-obesity effects of ginsenoside Rh2 are associated with the activation of AMPK signaling pathway in 3T3-L1 adipocyte. Biochem Biophys Res Commun 2007; 364: 1002-1008











