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Behavioral risk factor clusters among university students at nine universities in Libya

  • Received: 14 March 2018 Accepted: 20 June 2018 Published: 10 August 2018
  • Objectives: This study identifies and describes the clustering of 5 behavioral risk factors (BRFs) among university students. We also investigated whether cluster membership is associated with the students’ self-rated academic performance and self-rated health. Material and methods: A sample of 1300 undergraduates at 6 universities and 3 colleges in Libya completed a self-administered questionnaire that assessed BRFs (nutrition, physical activity, alcohol consumption, smoking, illicit drug use, inadequate sleep). A two-step cluster analysis generated student clusters with similar lifestyles. Results: Two contrasting clusters of almost even size emerged (after exclusion of alcohol and illicit drug use due to very low prevalence). Cluster 1 comprised students with higher engagement in all forms of physical activity, higher levels of health consciousness, greater daily fruit/vegetable intake and better sleep patterns than students in cluster 2. Only as regards the consumption of sweets, cluster 1 students had less favorable practices than cluster 2 students. The prevalence of smoking was equally low in both clusters. Students in cluster 2, depicting a less healthy lifestyle, were characterized by a higher proportion of women, of students with less income and of higher years of study. Belonging to cluster 2 was associated with lower self-rated health (OR: 0.46, p < 0.001) and with lower self-rated academic performance (OR: 0.66, p < 0.001). Conclusion: Preventive programs should not address BRFs in isolation and should particularly target students with clustering of BRFs using specifically tailored approaches.

    Citation: Walid El Ansari, Khalid A Khalil, Derrick Ssewanyana, Christiane Stock. Behavioral risk factor clusters among university students at nine universities in Libya[J]. AIMS Public Health, 2018, 5(3): 296-311. doi: 10.3934/publichealth.2018.3.296

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  • Objectives: This study identifies and describes the clustering of 5 behavioral risk factors (BRFs) among university students. We also investigated whether cluster membership is associated with the students’ self-rated academic performance and self-rated health. Material and methods: A sample of 1300 undergraduates at 6 universities and 3 colleges in Libya completed a self-administered questionnaire that assessed BRFs (nutrition, physical activity, alcohol consumption, smoking, illicit drug use, inadequate sleep). A two-step cluster analysis generated student clusters with similar lifestyles. Results: Two contrasting clusters of almost even size emerged (after exclusion of alcohol and illicit drug use due to very low prevalence). Cluster 1 comprised students with higher engagement in all forms of physical activity, higher levels of health consciousness, greater daily fruit/vegetable intake and better sleep patterns than students in cluster 2. Only as regards the consumption of sweets, cluster 1 students had less favorable practices than cluster 2 students. The prevalence of smoking was equally low in both clusters. Students in cluster 2, depicting a less healthy lifestyle, were characterized by a higher proportion of women, of students with less income and of higher years of study. Belonging to cluster 2 was associated with lower self-rated health (OR: 0.46, p < 0.001) and with lower self-rated academic performance (OR: 0.66, p < 0.001). Conclusion: Preventive programs should not address BRFs in isolation and should particularly target students with clustering of BRFs using specifically tailored approaches.


    Rice is a staple food in Indonesia, which is one of the largest rice producers in the world. According to BPS-Statistics Indonesia, rice production touched 54.60 million tons in 2019 [1]. Polished rice is the primary product of rice, of which rice bran is the main by-product, followed by rice husk and germ. Rice bran consists of 8-12 percent of the by-product from the rice milling process [2].

    Rice bran is used mainly as animal feed in Indonesia. There are not many studies on bioactivity, especially using animal model of diseases. Several studies show the potency of rice bran as food, especially as a functional ingredient, due to its beneficial bioactive compound content. The active bioactive compounds of rice bran are γ-oryzanol, polyphenols, phytosterols, tocopherols, tocotrienols, adenosine, ferulic acid, and adenosine, which can function as antioxidants and chemopreventive agents, with properties of lowering blood pressure and regulating cholesterol synthesis [3,4,5,6] Further, in some pigmented rice cultivars, rice bran is the part where the pigment is concentrated. The well-known pigmented rice in Indonesia is black rice. Black rice bran has a higher total phenolic content (TPC), anthocyanins, flavonoids, and antioxidant activity than polished red and white rice bran [7].

    Solid-state fermentation (SSF) is known to enhance the bioactive compounds of rice bran [8]. This method uses solid media for microbial growth. The advantages of SSF are avoidance of lipid hydrolysis, minimum water requirements, low risk of contamination, and high yield of fermentation product [9]. Earlier studies and our own showed that SSF, by using Rhizopus oligosporus, can increase TPC and antioxidant activity [10,11]. Further, our results showed that SSF with R. oligosporus offers the optimum fermentation conditions for rice bran in Inpari 30 and Cempo Ireng for 72 hours at 30 ℃ [11].

    The non-volatile compounds in rice bran have been studied in varieties of Calrose, Dixiebelle, and Neptune [12,13]. 453 compounds were found, consisting of amino acids, carbohydrates, vitamins and cofactors, lipids, nucleotides, peptides, secondary metabolites, and xenobiotics. Other studies have shown that fermentation treatment affects the number and diversity of bioactive compounds of rice bran [14]. Based on these findings, the non-volatile compounds of fermented and non-fermented rice bran may differ between rice varieties. Research has not been carried out on the non-volatile compounds in fermented and non-fermented bran, especially for rice bran varieties in Indonesia. Therefore, the purpose of this study was to analyze and compare non-volatile compounds of fermented and non-fermented rice bran of two varieties -i.e., Inpari 30 (IPR30) and Cempo Ireng (CI)- and their blood pressure lowering activity, by using a spontaneously hypertensive animal model. The IPR30 cultivar, another Ciherang cultivar (white rice) widely consumed in Indonesia and CI black rice cultivar, a variety of local pigmented rice planted in Bogor-West Java, Indonesia, were studied in this regard.

    The sample used in this study was brown rice IPR30 obtained from Indonesian Center for Rice Research, Indonesian Agency for Agricultural Research and Development, Ministry of Agriculture, Subang, West Java, Indonesia and paddy CI from the local farmer in Bogor, West Java, Indonesia. Paddy of CI was de-hulled by a Rice Machine-THU (Satake, Japan) to obtain brown rice. Two types of brown rice were polished by mini rice mill processing (Satake Grain Testing Mill, Hiroshima, Japan) as described previously [11]. The samples were divided into non-fermented IPR30 rice bran (IPRNF), fermented IPR30 rice bran (IPRF), non-fermented CI rice bran (CINF), and fermented CI rice bran (CIF).

    R. oligosporus were obtained from the Indonesian Culture Collection, Research Center for Biology, the Indonesian Institute of Science, Cibinong, Indonesia. The R. oligosporus were asseverated on potato dextrose agar media. The preparation of the culture and fermentation process followed the method used in a previous study [11]. The fermented and non-fermented samples were freeze-dried using a freeze-dryer (Labconco, USA) before further analysis.

    Sample extraction was done as described by [15,16], with modifications. Samples were dissolved in distilled water with 20% (w/v). The solutions were centrifuged (5223 x g, 10 minutes, 4 ℃) and then extracted by the solid phase extraction method. For every five mL of supernatant, one ml of lidocaine (internal standard) was added, resulting in 2.0083 µM of lidocaine in the supernatant. Thereafter, six ml of solution two was inserted into the cartridge (Oasis HLB 12 mL). Samples were vacuumed to remove their water and salt content. Samples were then eluted with methanol 5% and 1.5 mL were collected for analysis. For the animal study, the water extract of fermented RB was used by an oral single dose experiment.

    Non-volatile compounds were analyzed using Ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), as described in [12] with modifications. The liquid chromatography instrument used in this study was Waters ACQUITY UPLC H-Class System with C18 column (1.8 µm, 2.1 × 100 mm) at 50 ℃, while the mass spectrometry was Xevo G2-S quadrupole time-of-flight mass spectrometry (QToF-MS/MS) with electrospray ionization spray (ESI) system. For MS, the ion positive mode was used between 70-1000 m/z. Before injection, samples were filtered with a 0.2 µm syringe filter. Five µL of the sample was injected with mobile phase (A), 0.1% formic acid in water and (B), 0.1% formic acid in methanol (0% B to 70% B for 4 minutes, 70-98% B for 0.5 minutes, 98% B for 0.9 minutes). The observed injection flow rate was 0.2 mL per minute for 23 minutes. Masslynx v4.1 was used to identify the non-volatile compounds in the sample. The non-volatile compound data were then cross-checked with MassBank, Human Metabolome Database (HMDB) and Kyoto Encyclopedia of Genes and Genomes (KEGG) data [13]. The relative concentration of non-volatile compounds in the sample were determined by comparing the percentage area between sample and internal standard (lidocaine), based on the concentration of internal standard. The relative concentration was then converted into ppm units.

    The male SHRSP/Izumo strain (Japan SLC, Shizuoka, Japan) was used in these studies. The rats were housed in individual stainless-steel cages in a controlled atmosphere (temperature, 23 ± 2 ℃; humidity, 50 ± 10%; 12 h light-dark cycle) as per a previous study [4]. The Animal Research-Animal Care Committee approved the experimental plan for the present study of Tohoku University (2016AgA-024). The entire experiment was conducted following the guidelines issued by this committee and Japanese governmental legislation (2005). The water extract of fermented RB (CI and IPR30, 72 h fermentation) was used to determine the BP-lowering effect in SHRSP. The number of animals used in this study, concentration of the sample in the treated group, and control were similar to our previous study [11]. The blood pressure measurement was by the tail-cuff method with a BP meter as described in the previous study [4].

    The data are described as the mean ± SD. One way analysis of variance using SPSS version 22.0 was performed by two-way analysis (SPSS, Inc., Chicago, IL, USA) followed by Duncan's multiple range test for blood pressure study. The categorization of non-volatile compounds based on their relative concentration was analyzed by principal component analysis (PCA) with XLSTAT 2019.

    The non-volatile compounds of fermented and non-fermented rice bran of Inpari 30 and Cempo Ireng are presented in Supplementary Table 1. These were classified into 36 secondary metabolites, 16 lipids, 8 amino acids, 7 vitamins and cofactors, 3 peptides, one carbohydrate, and one nucleotide (Figure 1). Fermentation of Inpari 30 and Cempo Ireng rice bran produced new compounds that were not found in the non-fermented samples.

    Figure 1.  Non-volatile compounds of rice bran. Inpari 30 non-fermented (IPRNF); Inpari 30 fermented (IPRF); Cempo Ireng non-fermented (CINF); and Cempo Ireng fermented (CIF).

    The highest concentration of secondary metabolites found in IPRNF consisted of n, n-diethyl phenylacetamide (MS25), while in IPRF rice bran, the contents were dominated by 2-acetylpyrrole (MS29) and momilactone B (MS7). A study on n, n-diethyl phenylacetamide has shown that it can be used as an insect repellent [17] and 2-acetylpyrrole has hepatoprotective properties [18]. Several studies have shown momilactone B exhibiting inhibitory activities on α-amylase and α-glucosidase, as well as anti-cancer activities by increasing apoptosis in cancer cells [19,20]. In CINF rice bran, the dominant secondary metabolites were myrigalone A (MS36), kojic acid (MS9) and 4-methylbenzoic acid (MS11). Myrigalone A has been known to show antibacterial properties and kojic acid is a chelating agent produced during aerobic fungal fermentation [21].

    The most abundant compounds from the lipid in IPRNF and IPRF were leukotriene A4 (LD8) and aminocaproic acid (LD6). The dominant lipid compounds in CINF and CIF were lacinilene C 7-methyl ether (LD2) and phytosphingosine (LD9) respectively. Lacinilene C 7-methyl ether is known to have antibacterial properties [22]. Phytosphingosine has shown anti-inflammatory and antibacterial properties in skin disorders, besides playing a role in transcription activation in peroxisome proliferator-activated receptor [23,24].

    Amino acids with the highest concentration found in IPRNF and IPRF were norvaline (AA2) and l-phenylalanine (AA7) respectively. Norvaline is a byproduct of branched-chain amino acid synthesis, which can also act as arginase inhibitor [25]. L-phenylalanine is involved in neurotransmitters, hormones, and skin pigment synthesis in humans [26]. The highest concentration of amino acids in CINF and CIF were 3-methyldioxyindole (AA6) and indoleacrylic acid (AA8) respectively. Indoleacrylic acid has been known to be produced during tryptophan degradation.

    The dominant compounds found in the vitamins and cofactors group in IPRNF and IPRF were trigonelline (VK5) and pantothenic acid (VK2) respectively. Trigonelline is found only in IPRNF rice bran and is involved in treating diabetes by lowering the blood glucose level, increasing insulin sensitivity, and decreasing lipid peroxidation [27]. Pantothenic acid is synthesized by R. oligosporus from β-alanine and pantoic acid [28]. The dominant compound in the vitamins and cofactors in CINF and CIF were nicotinic acid (VK1) and 7-aminomethyl-7-carbaguanine (VK6), respectively. Nicotinic acid prevents atherosclerosis by increasing high-density lipoprotein, and decreasing triglyceride level and oxidative stress [29].

    Non-volatile compounds from the peptide group were detected only in the fermented samples. The most abundant peptide found in IPRF and CIF were phenylalanyl-isoleucine (PD3) and leucyl-isoleucine (PD2), respectively. According to an earlier study, Leucyl-isoleucine increases monocytes and platelet level in rats and stimulates AMPK phosphorylation [30,31].

    Principal component analysis (PCA) was applied to compare the differences of quantum in non-volatile compounds among the samples. The PCA of non-volatile compounds is shown in Figure 2. Non-fermented rice bran samples (IPRNF and CINF) were located in a quadrant different from fermented rice bran (IPRF and CIF), indicating that fermentation influenced non-volatile compound production. Adenosine (NA) generally was found the most in non-volatile compounds across all the samples. In the fermented sample of Inpari 30, the level of n, n-diethyl phenylacetamide (MS25), indoleacrylic acid (AA8), and l-phenylalanine (AA7) were higher, compared to non-fermented rice bran. Other major non-volatile compounds found in IPRNF samples were leukotriene A4 (LD8) and trigonelline (VK5).

    On the other hand, fermentation of the Cempo Ireng variety showed an increase in quercetin (MS15), isorhamnetin 7-glucoside (MS16), isorhamnetin (MS17), and nicotinic acid (VK1) levels. In Cempo Ireng samples, the non-volatile compounds with the highest concentration after adenosine were different. In CINF, it was myrigalone A (MS36), while CIF leucyl-isoleucine (PD2) and phenylalanyl-isoleucine (PD3) showed similar concentrations. These compounds are likely to have originated from arachidonic acid, nicotinic acid and nicotinamide, phenylalanine, tryptophan, and dipeptide metabolism. The major non-volatile compounds from each classification from PCA analysis are summarized in Figure 3. The list of non-volatile compounds and its statistical analyses shown in Supplementary Table 1 (Supplementary data).

    Adenosine is a compound necessary for production of energy within the body, and is created from purine metabolism. As a phytochemical found in rice bran, adenosine has the effect of lowering blood pressure, helps to treat hyperlipidemia, increases insulin activity, and preventing hypertension in the stroke-prone spontaneously hypertensive rat (SHRSP) [5]. In humans, adenosine has neuromodulator and neuroprotective functions, reduces epilepsy, and regulates the sleep cycle [32,33,34].

    Several studies of these compounds have shown them to have beneficial effects for the body, which includes lowering blood pressure, improving the immune and digestive systems, as well as having neuromodulator, neuroprotective, chemo preventive and antidiabetic properties. Further, other studies have also found that these bioactive compounds play a part in preventing gastric ulcer and improving hormone and melanin synthesis [26,27,30,32].

    Figure 2.  PCA plot non-volatile compounds of a) Inpari 30 (IPR) and b) Cempo Ireng (CI) (Fermented, F; and Non-Fermented, NF). The list of non-volatile compounds and its codes can be seen in Supplementary Table 1.
    Figure 3.  Summary of major non-volatile compounds (ppm). Inpari 30 non-fermented (IPRNF); Inpari 30 fermented (IPRF); Cempo Ireng non-fermented (CINF); and Cempo Ireng fermented (CIF).

    The proposed metabolic pathways found in rice bran are shown in Figure 4. Previous studies shown that rice bran has contained non-volatile compounds (12-14). Our study carried out non-volatile compound of fermented and non-fermented rice bran varieties in Indonesia. Pathways related to the compounds in the fermented and non-fermented Inpari 30 rice bran were the metabolism of valine and the citric acid cycle, respectively. Folate metabolism was found in fermented Cempo Ireng rice bran, while pentatonic acid, vitamin B6, and benzoxazinoid metabolism were found in non-fermented Cempo Ireng rice bran. Fermented versions of both fermented Inpari 30 and Cempo Ireng rice bran produced compounds from the metabolism of tyrosine, phenylalanine, pantothenic acid and dipeptide that was not detected in the non-fermented samples.

    Figure 4.  Proposed metabolic pathways of non-volatile compound of rice bran (a) Inpari 30 and (b) Cempo Ireng. (blue dots) fermented rice bran, (red dots) non-fermented rice bran, and (black dots) fermented and non-fermented rice bran.

    Non-volatile compounds in fermented Inpari 30 and Cempo Ireng rice brans were identified as metabolic pathways from tyrosine, phenylalanine, pantothenic acid, folic acid, dipeptide, terpenoid, and sphingolipid. The presence of dipeptide and amino acid compounds indicated that the samples were attributed to rice bran protein degradation by R. oligosporus-synthesized protease [35]. Similarly, metabolites of pantothenic and folic acid were also utilized by fungi, as they are components necessary for fungal metabolic activities [36]. Comparatively, compounds from sphingolipid metabolism are commonly found in fungal plasma membrane [37]. Fungi sphingolipids known to be involved in hyphal morphogenesis are produced during sphingolipid metabolism with serine and palmitoyl-CoA as its precursor [38,39], similar to the terpenoid found in fermented rice bran produced by the fungal mevalonate pathway [40].

    This study also investigated whether fermented RB showed any blood pressure-lowering effects after administration of a single oral dose (40 mg/kg body weight) (Table 1). Twelve-week-old male SHRSP with a systolic blood pressure (sBP) of approximately 170 mmHg, were used in this study. The result showed that there was similar sBP of the control group before and after administration. The sBP showed a significant decrease after 6h administration of IPRF (p < 0.05), compared to the control group. A blood pressure lowering activity was also found as sBP was decreasing from 2 h after administration until the end of the study. This study was consistent with the previous study by using Inpari 30 fermented RB [11]. Further, this study also showed evidence of adenosine as one of the identified bioactive compounds in rice bran [5].

    Table 1.  Time course of systolic blood pressure (mm/Hg) of fermented rice brana.
    Group 0 h 2 h 4 h 6 h
    Control 172.3 ± 13.1 172.0 ± 8.1 161.3 ± 6.5 168.0 ± 3.0
    CIF 176.8 ± 9.1 175.3 ± 2.9 165.3 ± 13.3 166.8 ± 8.5
    Change b (%) - +1.9 +2.4 −0.7
    IPRF 171.3 ± 5.0 152.3 ± 14.3 142.0 ± 12.4 141.5 ± 12.2*
    Change b (%) - −12.9 −13.6 −18.7
    Note: a Values are given as means ± SD, n = 4. *A significantly different (p < 0.05) versus Control after statistical analysis by one-way analysis of variance using SPSS version 22 software (SPSS, Inc., Chicago, IL, USA) followed by Duncan's multiple range test.

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    This study strengthened the proposition that IPRF is a good source of functional ingredient that can be effective in decreasing hypertension in an animal model of metabolic syndrome-related diseases. Future studies are required to specify the IPRF mechanism of blood pressure-lowering activity and other functionalities in relation to metabolic diseases.

    Different rice varieties and fermentation processes influence the concentration and types of non-volatile compounds in rice bran. Adenosine was found to have the greatest concentration of non-volatile compound in rice bran. Fermentation of rice bran samples from IPR30 and CI varieties generated compounds from tyrosine, phenylalanine, pentatonic acid, dipeptide, sphingolipid and terpenoid metabolism, which were not found in the non-fermented rice bran. Fermentation of rice bran can produce and enhance non-volatile compounds as anti-hypertensive effect in an animal model of hypertension. Further, this study found adenosine to be a useful marker for non-volatile compounds in rice bran.

    We would like to thank to the Ministry Research and Technology/BRIN RI for research funding. The partial of the research was supported by a grant from the collaboration research of JSPS and DIKTI RI.

    All authors declare no conflict of interest.

    Table Supplementary 1.  Non-volatile compounds detected in rice bran of Inpari 30 and Cempo Ireng by using UPLC-MS/MS.
    Compounds Codes HMDB ID Relative Concentrations (ppm) Effects References
    Inpari 30 Cempo Ireng
    Non-fermented Fermented Non-fermented Fermented
    (Amino acids)
    Meta-tyrosine AA1 0059720 ND 0.0266* ND ND Immunoprotective [41]
    Reduces metastasis [42]
    Norvaline AA2 0013716 0.0253* 0.0008* ND ND Arginase inhibitor [31]
    N-Acetyltryptophan AA3 0013713 ND 0.0039* ND ND Antioxidant [43]
    1H-Imidazole-1-acetic acid AA4 0029736 ND ND ND 0.0033* - -
    L-DOPA AA5 0000181 ND ND ND 0.0050* Treatment of Parkinson Dissease (by increasing dopamine levels in brain) [44]
    3-Methyldioxyindole AA6 0004186 ND ND 0.0011 ± 0.0003 ND - -
    L-Phenylalanine AA7 0000159 ND 0.2413 ± 0.2051a ND 0.0360 ± 0.0080b Neurotransmitter synthesis, hormones and pigments synthesis [26]
    Indoleacrylic acid AA8 0000734 0.0115*a 0.1806 ± 0.1412b ND 0.0395 ± 0.0011a Improves the instentines functions [45]
    (Carbohydrates)
    Succinic acid KH 0000254 0.0002* ND ND ND Antioxidant, Imrpove the immune and nervous functions [46]
    (Lipids)
    Cincassiol B LD1 0036855 ND 0, 0208* ND ND - -
    Lacinilene C 7-methyl ether LD2 0036456 0.0129 ± 0.0015 0.0058* 0.0134* 0.0023* Antimicrobial [22]
    Valdiic acid LD3 0040980 ND 0.0088 ± 0.0108 ND ND - -
    Prostaglandin C1(1-) LD4 0062756 0.0102 ± 0.0029 ND 0.0090 ± 0.0017 ND - -
    10-Oxo-11-octadecen-13-olide LD5 0029786 0.0041* ND 0.0109* ND - -
    Aminocaproic acid LD6 0001901 ND 0.0390* ND 0.0037* Antifibrinolytic [47]
    L-Octanoylcarnitine LD7 0000791 ND 0.0180* 0.0091 ± 0.0052 ND - -
    Leukotriene A4 LD8 0029016 0.0352 ± 0.0288 0.0131 ± 0.0063 0.0110* ND The parent molecule for the biosynthesis of all leukotrienes [48]
    Phytosphingosine LD9 0004610 ND 0.0126*b 0.0114 ± 0.0031a 0.0049 ± 0.0042b ● Anti-inlammatory and antibacterial in skin disorders [31]
    ● Activates the transcription activity on PPAR [23]
    (Ent-2alpha, 3beta, 15beta, 16beta)-15, 16-Epoxy-2, 3-kauranediol LD10 0038688 0.0201 ± 0.0099b ND 0.0019*a ND - -
    Dehydroabietic acid LD11 0031127 0.0263* ND ND ND ● Anti-inflammatory in obese people [49]
    ● Activates the SIRT1 enzymes [50]
    13, 14-Dihydro-15-keto-PGE2 LD12 0002776 ND ND 0.0010* ND Increases the growth of pancreatic celss [51]
    3-hydroxyundecanoyl carnitine LD13 0061637 ND ND 0.0102 ± 0.0031 ND - -
    Leukotriene C4 LD14 0001198 0.0095* ND ND ND Lipid mediator for inflammation [52]
    5-Hexyltetrahydro-2-furanoctanoic acid LD15 0029018 0.0105* ND 0.0021* ND - -
    (Z)-13-Oxo-9-octadecenoic acid LD16 0029796 0.0094* 0.0072* ND ND - -
    (Nucleotides)
    Adenosine NA 0000050 0.0838 ± 0.1053 0.4323 ± 0.1236 0.2119 ± 0.0142 0.3007 ± 0.1602 ● Neuromodulator [34]
    ● Neuroprotective [33]
    ● Reduces epilepsy [32]
    ● Regulates the sleep cycle [53]
    ● Lowering blood pressure [5]
    (Secondary Metabolites)
    Cohumulone MS1 0033981 ND 0.0052* ND ND Aldo keto reductase inhibitors [54]
    3-O-Methylmethyldopa MS2 0142154 ND 0.0022 ± 0.0005 ND ND - -
    2, 6-Dimethoxy-4-propylphenol MS3 0036226 ND 0.0007 ± 0.0001 ND ND - -
    Alpha-curcumene MS4 0059878 ND 0.0017±0.0004 ND ND ● Antimicrobial [55]
    ● Induced apoptosis [56]
    Cuscohygrine MS5 0030290 ND 0.0033* 0.0051* 0.0028* - -
    3-Tert-butyl-4-hydroxyanisole MS6 0059925 ND 0.0015* 0.0184* ND The building blocks of butylated hydroxyanisole (BHA) [57]
    Momilactone B MS7 0036749 ND 0.0153* ND ND ● α-Amylase and α-Glucosidase inhibitors [20]
    ● Cancer chemopreventive [19]
    2-Indolecarboxylic acid MS8 0002285 0.0024* ND 0.0023* ND Antioxidant [58]
    Kojic acid MS9 0032923 0.0061 ± 0.0016 ND 0.0103 ± 0.0010 ND ● Tyrosinase inhibitors [59]
    ● Immunomodulator [9]
    L-1, 2, 3, 4-Tetrahydro-beta-carboline-3-carboxylic acid MS10 0035665 0.0008* ND ND ND - -
    4-Methylbenzoic acid MS11 0029635 0.0010*a ND ND 0.0385 ± 0.0103b - -
    2-Methylhippuric acid MS12 0011723 0.0006* ND ND ND - -
    Momilactone A MS13 0036748 0.0020* ND ND ND ● α-Amylase and α-Glucosidase inhibitors [20]
    Coumarin MS14 0001218 0.0009* ND ND ND ● Antimicrobial [60)
    ● Acetylcholinesterase (AChE) inhibitor [61]
    Quercetin MS15 0005794 ND ND 0.0050 ± 0.0031 0.0057 ± 0.0028 ● Antioxidant [62]
    ● Decreases activation of dendytic celss for the treatment of inflammation, autoimmunity and transplantation [61]
    ● Antiviral activity against dengue fever [63]
    ● Lowering blood pressure in people with hypertension [64]
    ● Reduces symptoms of non-alcoholic fatty liver dissease [65]
    Isorhamnetin 7-glucoside MS16 0029479 ND ND 0.0089 ± 0.0050 0.0165 ± 0.0009 Antioxidant [66]
    Isorhamnetin MS17 0002655 ND ND 0.0048* 0.0121* Treats cerebral vascular complications associated with diabetes [67]
    2-Hydroxy-2-phenylpropanoic acid MS18 0142137 ND ND 0.0045 ± 0.0007a 0.0029 ± 0.0013b - -
    2-Phenylpropionaldehyde dimethyl acetal MS19 0032468 ND ND ND 0.0055 ± 0.0022 - -
    Naringenin MS20 0002670 ND ND ND 0.0037* ● Hepatoprotector [68]
    ● Reduces TNF- α production [69]
    ● Anti-hyperglycemia [70]
    ● Cardioprotective [71]
    ● Antiviral activity against dengue fever [72]
    ● Inhibits the proliferation and migration of prostate cancer cells [73]
    Phenprocoumon MS21 0015081 ND ND ND 0.0058* ● Anticoagulant [74]
    Isovanillic acid MS22 0060003 ND ND 0.0042 ± 0.0011 ND ● Antibacterial [75]
    ● Antioxidant [76]
    Antimicrobial [60]
    2, 6-Dimethoxybenzoic acid MS23 0029273 ND ND 0.0106* ND - -
    Benzoic acid MS24 0001870 ND ND 0.0009 ± 0.0003 ND Inhibits the growth of resistant bacteria [77]
    N, N-diethyl phenylacetamide MS25 0032635 0.0090* 0.0096* 0.0066* 0.0263* Mosquitos repellent [17]
    Oryzalide B MS27 0037592 ND ND ND 0.0053 ± 0.0032 Antibacterial [78]
    Acetylvalerenolic acid MS28 0035687 ND ND ND 0.0045* - -
    MS29 0035882 ND 0.0309 ND ND Hepatoprotector [18]
    Dimboa-glc MS30 0029710 ND ND 0.0089 ± 0.0056 ND - -
    2-Decylfuran MS31 0032215 ND ND ND 0.0015 - -
    Piperenol A triacetate MS32 0041535 ND 0.0129* ND ND - -
    Ginsenoyne G MS33 0039589 ND ND 0.0025 ND - -
    Acetylpterosin C MS34 0030764 0.0053* ND ND ND - -
    1, 3, 11-Tridecatriene-5, 7, 9-triyne MS35 0034294 ND ND 0.0160 ND - -
    Myrigalone A MS36 0037245 ND ND 0.0278* 0.0256* Antibacterial [79]
    (Vitamins dan cofactors)
    Nicotinic acid VK1 0001488 0.0114 ± 0.0007 ND 0.0060 ± 0.0025 0.0076 ± 0.0009 Increases HDL cholesterol and lowers triglycerides for the treatment of atherosclerosis [29]
    Pantothenic acid VK2 0000210 ND ND ND 0.0028 ± 0.0010 Substrates for the synthesis of coenzyme A and ACP (acyl carrier protein) [80]
    2-Hydroxypyridine VK3 0013751 0.0008* ND ND ND - -
    4-Methyl-5-thiazoleethanol VK4 - 0.0175 ± 0.0014 ND 0.0066 ± 0.0021 ND - -
    Trigonelline VK5 0000875 0.0344 ± 0.0247 ND ND ND ● Increases cell sensitivity to anticancer and apoptotic drugs [81]
    ● Prevents gastric ulcer induced by indomethacin [82]
    ● Lowering blood sugar and lipid as well as increasing insulin sensitivity for diabetes
    ● Inhibits neurons loss in hypocampus [83]
    7-Aminomethyl-7-carbaguanine VK6 0011690 ND ND ND 0.0132* - -
    Pyridoxal VK7 0001545 ND ND 0.0066 ± 0.0021 ND ● Cofactors in various amino acids metabolism [84]
    ● Maintains the nervous systems in infants [85]
    (Peptides)
    Leucyl-valine PD1 0028942 ND 0.0222 ± 0.0162 ND ND Increases the expression of glutathione peroxidase, antioxidants and cell protection agents [86]
    Leucyl-isoleucine PD2 0028932 ND 0.0653 ± 0.0436 ND 0.0596 ± 0.0263 Increases the stimulation of AMPK phosphorylation (5'-AMP protein kinase), monocytes, and platelets [30]
    Note: The presentation of the relative value data for the compounds comes from the calculation of the average relative area of the compound from 3 replications ± deviation standard; ND = Not Detected; * = compound obtained only in 1 replication; Numbers on the same line with different letters indicate significant differences (p < 0.05).

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