Displaying publications 21 - 40 of 167 in total

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  1. Fulltext Authentication of Nigella sativa seed oil in binary and ternary mixtures with corn oil and soybean oil using FTIR spectroscopy coupled with partial least square
    Rohman A, Ariani R
    ScientificWorldJournal, 2013;2013:740142.
    PMID: 24319381 DOI: 10.1155/2013/740142
    Fourier transform infrared spectroscopy (FTIR) combined with multivariate calibration of partial least square (PLS) was developed and optimized for the analysis of Nigella seed oil (NSO) in binary and ternary mixtures with corn oil (CO) and soybean oil (SO). Based on PLS modeling performed, quantitative analysis of NSO in binary mixtures with CO carried out using the second derivative FTIR spectra at combined frequencies of 2977-3028, 1666-1739, and 740-1446 cm(-1) revealed the highest value of coefficient of determination (R (2), 0.9984) and the lowest value of root mean square error of calibration (RMSEC, 1.34% v/v). NSO in binary mixtures with SO is successfully determined at the combined frequencies of 2985-3024 and 752-1755 cm(-1) using the first derivative FTIR spectra with R (2) and RMSEC values of 0.9970 and 0.47% v/v, respectively. Meanwhile, the second derivative FTIR spectra at the combined frequencies of 2977-3028 cm(-1), 1666-1739 cm(-1), and 740-1446 cm(-1) were selected for quantitative analysis of NSO in ternary mixture with CO and SO with R (2) and RMSEC values of 0.9993 and 0.86% v/v, respectively. The results showed that FTIR spectrophotometry is an accurate technique for the quantitative analysis of NSO in binary and ternary mixtures with CO and SO.
    Matched MeSH terms: Least-Squares Analysis
  2. Fulltext An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification
    Siddiqui MF, Reza AW, Kanesan J
    PLoS One, 2015;10(8):e0135875.
    PMID: 26280918 DOI: 10.1371/journal.pone.0135875
    A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI) as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT), principal component analysis (PCA), and least squares support vector machine (LS-SVM) are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF) kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients' benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%). Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities from the individual subjects, therefore, it can be used as a significant tool in clinical practice.
    Matched MeSH terms: Least-Squares Analysis
  3. Fulltext Alpha-Glucosidase Inhibitory Effect of Psychotria malayana Jack Leaf: A Rapid Analysis Using Infrared Fingerprinting
    Nipun TS, Khatib A, Ahmed QU, Redzwan IE, Ibrahim Z, Khan AYF, et al.
    Molecules, 2020 Sep 11;25(18).
    PMID: 32932994 DOI: 10.3390/molecules25184161
    The plant Psychotria malayana Jack belongs to the Rubiaceae family and is known in Malaysia as "meroyan sakat/salung". A rapid analytical technique to facilitate the evaluation of the P. malayana leaves' quality has not been well-established yet. This work aimed therefore to develop a validated analytical technique in order to predict the alpha-glucosidase inhibitory action (AGI) of P. malayana leaves, applying a Fourier Transform Infrared Spectroscopy (FTIR) fingerprint and utilizing an orthogonal partial least square (OPLS). The dried leaf extracts were prepared by sonication of different ratios of methanol-water solvent (0, 25, 50, 75, and 100% v/v) prior to the assessment of alpha-glucosidase inhibition (AGI) and the following infrared spectroscopy. The correlation between the biological activity and the spectral data was evaluated using multivariate data analysis (MVDA). The 100% methanol extract possessed the highest inhibitory activity against the alpha-glucosidase (IC50 2.83 ± 0.32 μg/mL). Different bioactive functional groups, including hydroxyl (O-H), alkenyl (C=C), methylene (C-H), carbonyl (C=O), and secondary amine (N-H) groups, were detected by the multivariate analysis. These functional groups actively induced the alpha-glucosidase inhibition effect. This finding demonstrated the spectrum profile of the FTIR for the natural herb P. malayana Jack, further confirming its medicinal value. The developed validated model can be used to predict the AGI of P. malayana, which will be useful as a tool in the plant's quality control.
    Matched MeSH terms: Least-Squares Analysis
  4. Fulltext 1H-NMR-Based Metabolomics: An Integrated Approach for the Detection of the Adulteration in Chicken, Chevon, Beef and Donkey Meat
    Akhtar MT, Samar M, Shami AA, Mumtaz MW, Mukhtar H, Tahir A, et al.
    Molecules, 2021 Jul 30;26(15).
    PMID: 34361796 DOI: 10.3390/molecules26154643
    Meat is a rich source of energy that provides high-value animal protein, fats, vitamins, minerals and trace amounts of carbohydrates. Globally, different types of meats are consumed to fulfill nutritional requirements. However, the increasing burden on the livestock industry has triggered the mixing of high-price meat species with low-quality/-price meat. This work aimed to differentiate different meat samples on the basis of metabolites. The metabolic difference between various meat samples was investigated through Nuclear Magnetic Resonance spectroscopy coupled with multivariate data analysis approaches like principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA). In total, 37 metabolites were identified in the gluteal muscle tissues of cow, goat, donkey and chicken using 1H-NMR spectroscopy. PCA was found unable to completely differentiate between meat types, whereas OPLS-DA showed an apparent separation and successfully differentiated samples from all four types of meat. Lactate, creatine, choline, acetate, leucine, isoleucine, valine, formate, carnitine, glutamate, 3-hydroxybutyrate and α-mannose were found as the major discriminating metabolites between white (chicken) and red meat (chevon, beef and donkey). However, inosine, lactate, uracil, carnosine, format, pyruvate, carnitine, creatine and acetate were found responsible for differentiating chevon, beef and donkey meat. The relative quantification of differentiating metabolites was performed using one-way ANOVA and Tukey test. Our results showed that NMR-based metabolomics is a powerful tool for the identification of novel signatures (potential biomarkers) to characterize meats from different sources and could potentially be used for quality control purposes in order to differentiate different meat types.
    Matched MeSH terms: Least-Squares Analysis
  5. Fulltext Correlation of FT-IR Fingerprint and α-Glucosidase Inhibitory Activity of Salak (Salacca zalacca) Fruit Extracts Utilizing Orthogonal Partial Least Square
    Saleh MSM, Siddiqui MJ, Mat So'ad SZ, Roheem FO, Saidi-Besbes S, Khatib A
    Molecules, 2018 06 13;23(6).
    PMID: 29899270 DOI: 10.3390/molecules23061434
    Salak fruit (Salacca zalacca), commonly known as snake fruit, is used indigenously as food and for medicinal applications in Southeast Asia. This study was conducted to evaluate the α-glucosidase inhibitory activity of salak fruit extracts in correlation to its Fourier transform infrared spectroscopy (FT-IR) fingerprint, utilizing orthogonal partial least square. This calibration model was applied to develop a rapid analytical method tool for quality control of this fruit. A total of 36 extracts prepared with different solvent ratios of ethanol⁻water (100, 80, 60, 40.20, 0% v/v) and their α-glucosidase inhibitory activities determined. The FT-IR spectra of ethanol⁻water extracts measured in the region of 400 and 4000 cm−1 at a resolution of 4 cm−1. Multivariate analysis with a combination of orthogonal partial least-squares (OPLS) algorithm was used to correlate the bioactivity of the samples with the FT-IR spectral data. The OPLS biplot model identified several functional groups (C⁻H, C=O, C⁻N, N⁻H, C⁻O, and C=C) which actively induced α-glucosidase inhibitory activity.
    Matched MeSH terms: Least-Squares Analysis
  6. Fulltext Novel biphenyl ester derivatives as tyrosinase inhibitors: Synthesis, crystallographic, spectral analysis and molecular docking studies
    Kwong HC, Chidan Kumar CS, Mah SH, Chia TS, Quah CK, Loh ZH, et al.
    PLoS One, 2017;12(2):e0170117.
    PMID: 28241010 DOI: 10.1371/journal.pone.0170117
    Biphenyl-based compounds are clinically important for the treatments of hypertension and inflammatory, while many more are under development for pharmaceutical uses. In the present study, a series of 2-([1,1'-biphenyl]-4-yl)-2-oxoethyl benzoates, 2(a-q), and 2-([1,1'-biphenyl]-4-yl)-2-oxoethyl pyridinecarboxylate, 2(r-s) were synthesized by reacting 1-([1,1'-biphenyl]-4-yl)-2-bromoethan-1-one with various carboxylic acids using potassium carbonate in dimethylformamide at ambient temperature. Single-crystal X-ray diffraction studies revealed a more closely packed crystal structure can be produced by introduction of biphenyl moiety. Five of the compounds among the reported series exhibited significant anti-tyrosinase activities, in which 2p, 2r and 2s displayed good inhibitions which are comparable to standard inhibitor kojic acid at concentrations of 100 and 250 μg/mL. The inhibitory effects of these active compounds were further confirmed by computational molecular docking studies and the results revealed the primary binding site is active-site entrance instead of inner copper binding site which acted as the secondary binding site.
    Matched MeSH terms: Least-Squares Analysis
  7. Psychosocial stressors at work and well-being of male employees
    Noor Dalila IZA, Rosnah I, Ismail NH
    Med J Malaysia, 2019 04;74(2):160-167.
    PMID: 31079128
    INTRODUCTION: Psychosocial stressors appear to alter the state of mind and adoption of overeating behaviour, resulting in high body mass index. This study was conducted to determine the magnitude of psychosocial stressors on male employees' well-being.

    METHOD: This study used secondary data retrieved from a cross-sectional study involving 492 male employees' completed data. Eligible participants completed validated questionnaires of the Psychosocial Safety Climate (PSC-12) scale, short version Demand Induced Strain Compensation (DISQ 2.1), Oldenburg Burnout Inventory - Emotional Exhaustion domain and the Three Eating Factor Questionnaire (TEFQ) -Uncontrolled Eating domain; assessing psychosocial safety climate, job demands and job resources, emotional exhaustion, and uncontrolled eating behaviour, respectively. Body mass index (BMI) was calculated based on weight and height. The research statistical model was tested by two-steps of assessment replicating partial least squares structural equation modelling (PLS-SEM).

    RESULT: The results show that psychosocial stressors (psychosocial safety climate, job demands and job resources) had significant effects on emotional exhaustion (β= -0.149, p=0.004; β= 0.223, p<0.001; β= -0.127, p=0.013). Emotional exhaustion predicted by work stressors may act as a chain reaction which could result in uncontrolled eating (β=0.138, p=0.005) and high BMI (β=0.185, p<0.001). Emotional exhaustion does mediate the relationship between PSC and uncontrolled eating behaviour (β= -0.021 [95% boot CI bias corrected: -0.048, -0.002]).

    CONCLUSION: The psychosocial stressors at work are significant factors for emotional exhaustion, which further signifies the positive effect on uncontrolled eating behaviour and BMI among Malaysian male employees.

    Matched MeSH terms: Least-Squares Analysis
  8. Fulltext Heat stress modifies the lactational performances and the urinary metabolomic profile related to gastrointestinal microbiota of dairy goats
    Contreras-Jodar A, Nayan NH, Hamzaoui S, Caja G, Salama AAK
    PLoS One, 2019;14(2):e0202457.
    PMID: 30735497 DOI: 10.1371/journal.pone.0202457
    The aim of the study is to identify the candidate biomarkers of heat stress (HS) in the urine of lactating dairy goats through the application of proton Nuclear Magnetic Resonance (1H NMR)-based metabolomic analysis. Dairy does (n = 16) in mid-lactation were submitted to thermal neutral (TN; indoors; 15 to 20°C; 40 to 45% humidity) or HS (climatic chamber; 37°C day, 30°C night; 40% humidity) conditions according to a crossover design (2 periods of 21 days). Thermophysiological traits and lactational performances were recorded and milk composition analyzed during each period. Urine samples were collected at day 15 of each period for 1H NMR spectroscopy analysis. Principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) assessment with cross validation were used to identify the goat urinary metabolome from the Human Metabolome Data Base. HS increased rectal temperature (1.2°C), respiratory rate (3.5-fold) and water intake (74%), but decreased feed intake (35%) and body weight (5%) of the lactating does. No differences were detected in milk yield, but HS decreased the milk contents of fat (9%), protein (16%) and lactose (5%). Metabolomics allowed separating TN and HS urinary clusters by PLS-DA. Most discriminating metabolites were hippurate and other phenylalanine (Phe) derivative compounds, which increased in HS vs. TN does. The greater excretion of these gut-derived toxic compounds indicated that HS induced a harmful gastrointestinal microbiota overgrowth, which should have sequestered aromatic amino acids for their metabolism and decreased the synthesis of neurotransmitters and thyroid hormones, with a negative impact on milk yield and composition. In conclusion, HS markedly changed the thermophysiological traits and lactational performances of dairy goats, which were translated into their urinary metabolomic profile through the presence of gut-derived toxic compounds. Hippurate and other Phe-derivative compounds are suggested as urinary biomarkers to detect heat-stressed dairy animals in practice.
    Matched MeSH terms: Least-Squares Analysis
  9. Fulltext Identification of Antidiabetic Metabolites from Paederia foetida L. Twigs by Gas Chromatography-Mass Spectrometry-Based Metabolomics and Molecular Docking Study
    Tan DC, Kassim NK, Ismail IS, Hamid M, Ahamad Bustamam MS
    Biomed Res Int, 2019;2019:7603125.
    PMID: 31275982 DOI: 10.1155/2019/7603125
    Paederia foetida L. (Rubiaceae) is a climber which is widely distributed in Asian countries including Malaysia. The plant is traditionally used to treat various diseases including diabetes. This study is to evaluate the enzymatic inhibition activity of Paederia foetida twigs extracts and to identify the metabolites responsible for the bioactivity by gas chromatography-mass spectrometry (GC-MS) metabolomics profiling. Three different twig extracts, namely, hexane (PFH), chloroform (PFC), and methanol (PFM), were submerged for their α-amylase and α-glucosidase inhibition potential in 5 replicates for each. Results obtained from the loading column scatter plot of orthogonal partial least square (OPLS) model revealed the presence of 12 bioactive compounds, namely, dl-α-tocopherol, n-hexadecanoic acid, 2-hexyl-1-decanol, stigmastanol, 2-nonadecanone, cholest-8(14)-en-3-ol, 4,4-dimethyl-, (3β,5α)-, stigmast-4-en-3-one, stigmasterol, 1-ethyl-1-tetradecyloxy-1-silacyclohexane, ɣ-sitosterol, stigmast-7-en-3-ol, (3β,5α,24S)-, and α-monostearin. In silico molecular docking was carried out using the crystal structure α-amylase (PDB ID: 4W93) and α-glucosidase (PDB ID: 3WY1). α-Amylase-n-hexadecanoic acid exhibited the lowest binding energy of -2.28 kcal/mol with two hydrogen bonds residue, namely, LYS178 and TYR174, along with hydrophobic interactions involving PRO140, TRP134, SER132, ASP135, and LYS172. The binding interactions of α-glucosidase-n-hexadecanoic acid complex ligand also showed the lowest binding energy among 5 major compounds with the energy value of -4.04 kcal/mol. The complex consists of one hydrogen bond interacting residue, ARG437, and hydrophobic interactions with ALA444, ASP141, GLN438, GLU432, GLY374, LEU373, LEU433, LYS352, PRO347, THR445, HIS348, and PRO351. The study provides informative data on the potential antidiabetic inhibitors identified in Paederia foetida twigs, indicating the plant has the therapeutic effect properties to manage diabetes.
    Matched MeSH terms: Least-Squares Analysis
  10. Fulltext Evaluation of antidiabetic properties of Momordica charantia in streptozotocin induced diabetic rats using metabolomics approach
    Perumal, V., Khoo, W.C., Abdul-Hamid, A., Ismail, A., Saari, K., Murugesu, S., et al.
    International Food Research Journal, 2015;22(3):1298-1306.
    MyJurnal
    Momordica charantia, also known as bitter melon or ‘peria katak’ in Malaysia, is a member of the family Cucurbitaceae. Bitter melon is an excellent source of vitamins and minerals that made it extensively nutritious. Moreover, the seed, fruit and leave of the plant contain bioactive compounds with a wide range of biological activities that have been used in traditional medicines in the treatment of several diseases, including inflammation, infections, obesity and diabetes. The aim of this study was to evaluate changes in urinary metabolite profile of the normal, streptozotocin-induced type 1 diabetes and M. charantia treated diabetic rats using proton nuclear magnetic resonance (1H-NMR) -based metabolomics profiling. Study had been carried out by inducing diabetes in the rats through injection of streptozotocin, which exhibited type 1 diabetes. M. charantia extract (100 and 200 mg/kg body weight) was administrated to the streptozotocin-induced diabetic rats for one week. Blood glucose level after administration was measured to examine hypoglycemic effect of the extract. The results obtained indicated that M. charantia was effective in lowering blood glucose level of the diabetic rats. The loading plot of Partial Least Square (PLS) component 1 showed that diabetic rats had increased levels of lactate and glucose in urine whereas normal and the extract treated diabetic rats had higher levels of succinate, creatine, creatinine, urea and phenylacetylglycine in urine. While the loading plot of PLS component 2 showed a higher levels of succinate, citrate, creatine, creatinine, sugars, and hippurate in urine of normal rat compared to the extract treated diabetic rat. Administration of M. charantia extract was found to be able to regulate the altered metabolic processes. Thus, it could be potentially used to treat the diabetic patients.
    
    Matched MeSH terms: Least-Squares Analysis
  11. Stereoselective method development and validation for determination of concentrations of amphetamine-type stimulants and metabolites in human urine using a simultaneous extraction-chiral derivatization approach
    Wan Raihana WA, Gan SH, Tan SC
    J Chromatogr B Analyt Technol Biomed Life Sci, 2011 Jan 1;879(1):8-16.
    PMID: 21147046 DOI: 10.1016/j.jchromb.2010.10.037
    Amphetamine-type stimulants (ATS) are a group of chiral amine drugs which are commonly abused for their sympathomimetic and stimulant properties. ATS are extensively metabolised by hepatic cytochrome P450 enzymes. As metabolism of ATS has been shown to be highly stereospecific, stereoselective analytical methods are essential for the quantitative determination of ATS concentrations for both in vivo and in vitro studies of ATS metabolism. This paper describes a new stereoselective method for the simultaneous determination of amphetamine (AM), methamphetamine (MA), 3,4-methylenedioxymethamphetamine (MDMA), 3,4-methylenedioxyamphetamine (MDA), 4-hydroxy-3-methoxymethamphetamine (HMMA), 4-hydroxy-3-methoxyamphetamine (HMA), 3,4-hydroxymethamphetamine (HHMA) and 3,4-hydroxyamphetamine (HHA) in human urine samples validated according to the United States Food and Drug Administration guidelines. In this method, analytes are simultaneously extracted and derivatized with R-(-)-α-methoxy-α-(trifluoromethyl)phenylacetyl chloride (R-MTPCl) as the chiral derivatization reagent. Following this, the analytes were subjected to a second derivatization with N-methyl-N-trimethylsilyltrifluoroacetamide (MSTFA) which targets the hydroxyl groups present in HMMA, HMA, HHMA and HHA. The derivatized analytes were separated and quantified using gas chromatography-mass spectrometry (GC-MS). The method was evaluated according to the established guidelines for specificity, linearity, precision, accuracy, recovery and stability using a five-day protocol. Intra-day precision ranged from 0.89 to 11.23% RSD whereas inter-day precision was between 1.03 and 12.95% RSD. Accuracy values for the analytes ranged from -5.29% to 13.75%. Limits of quantitation were 10 μg/L for AM, MA, MDMA, HMA and HMMA and 2μg/L for MDA, HMA and HHA. Recoveries and stability values were also within accepted values. The method was applied to authentic ATS-positive samples.
    Matched MeSH terms: Least-Squares Analysis
  12. Designing hypothesis of substituted benzoxazinones as HIV-1 reverse transcriptase inhibitors: QSAR approach
    Veerasamy R, Subramaniam DK, Chean OC, Ying NM
    J Enzyme Inhib Med Chem, 2012 Oct;27(5):693-707.
    PMID: 21961709 DOI: 10.3109/14756366.2011.608664
    A linear quantitative structure activity relationship (QSAR) model is presented for predicting human immunodeficiency virus-1 (HIV-1) reverse transcriptase enzyme inhibition. The 2D QSAR and 3D-QSAR models were developed by stepwise multiple linear regression, partial least square (PLS) regression and k-nearest neighbor-molecular field analysis, PLS regression, respectively using a database consisting of 33 recently discovered benzoxazinones. The primary findings of this study is that the number of hydrogen atoms, number of (-NH2) group connected with solitary single bond alters the inhibition of HIV-1 reverse transcriptase. Further, presence of electrostatic, hydrophobic and steric field descriptors significantly affects the ability of benzoxazinone derivatives to inhibit HIV-1 reverse transcriptase. The selected descriptors could serve as a primer for the design of novel and potent antagonists of HIV-1 reverse transcriptase.
    Matched MeSH terms: Least-Squares Analysis
  13. Measurement and dimension of road fatality in Brunei
    Haque MO
    Int J Inj Contr Saf Promot, 2011 Mar;18(1):45-55.
    PMID: 21409677 DOI: 10.1080/17457300.2010.517319
    In this article, we have investigated the pattern of road fatality in Brunei. It is seen from this analysis that road fatality in Brunei was one of the highest in the world in the early 1990s, but has been significantly reduced over the years, and is now one of the lowest in the world. Preliminary investigation shows that young male drivers are responsible for most road fatalities in Brunei. We have also fitted a linear regression model and found that road fatality is significantly positively related to people aged 18-24 years and new registered vehicles, both of which are expected to grow with the growth of population and economic development. Hence, road fatality in Brunei is also expected to grow unless additional effective road safety countermeasures are introduced and implemented to reduce road toll. Negative coefficient is observed for trend variable, indicating the reduction of road fatality due to the combined effects of improvements of vehicle safety, road design, medical facilities and road safety awareness among road user groups. However, short-term road fatality analysis based on monthly data indicates that the coefficient of the trend variable is positive, implying that in recent months road fatalities are increasing in Brunei, which is supported by media reports. We have compared Brunei's road fatality data with Australia, Singapore and Malaysia and found that Brunei's road fatality rate is lower than Singapore and Malaysia, but higher than Australia. This indicates that there are still opportunities to reduce road fatalities in Brunei if additional effective road safety strategies are implemented like in Australia without interfering in the economic and social development of Brunei.
    Matched MeSH terms: Least-Squares Analysis
  14. Influence of Different Drying Treatments and Extraction Solvents on the Metabolite Profile and Nitric Oxide Inhibitory Activity of Ajwa Dates
    Abdul-Hamid NA, Abas F, Ismail IS, Shaari K, Lajis NH
    J Food Sci, 2015 Nov;80(11):H2603-11.
    PMID: 26457883 DOI: 10.1111/1750-3841.13084
    This study aimed to examine the variation in the metabolite profiles and nitric oxide (NO) inhibitory activity of Ajwa dates that were subjected to 2 drying treatments and different extraction solvents. (1)H NMR coupled with multivariate data analysis was employed. A Griess assay was used to determine the inhibition of the production of NO in RAW 264.7 cells treated with LPS and interferon-γ. The oven dried (OD) samples demonstrated the absence of asparagine and ascorbic acid as compared to the freeze dried (FD) dates. The principal component analysis showed distinct clusters between the OD and FD dates by the second principal component. In respect of extraction solvents, chloroform extracts can be distinguished by the absence of arginine, glycine and asparagine compared to the methanol and 50% methanol extracts. The chloroform extracts can be clearly distinguished from the methanol and 50% methanol extracts by first principal component. Meanwhile, the loading score plot of partial least squares analysis suggested that beta glucose, alpha glucose, choline, ascorbic acid and glycine were among the metabolites that were contributing to higher biological activity displayed by FD and methanol extracts of Ajwa. The results highlight an alternative method of metabolomics approach for determination of the metabolites that contribute to NO inhibitory activity.
    Matched MeSH terms: Least-Squares Analysis
  15. Multivariate analysis of PRISMA optimized TLC image for predicting antioxidant activity and identification of contributing compounds from Pereskia bleo
    Sharif KM, Rahman MM, Azmir J, Khatib A, Sabina E, Shamsudin SH, et al.
    Biomed Chromatogr, 2015 Dec;29(12):1826-33.
    PMID: 26033701 DOI: 10.1002/bmc.3503
    Multivariate analysis of thin-layer chromatography (TLC) images was modeled to predict antioxidant activity of Pereskia bleo leaves and to identify the contributing compounds of the activity. TLC was developed in optimized mobile phase using the 'PRISMA' optimization method and the image was then converted to wavelet signals and imported for multivariate analysis. An orthogonal partial least square (OPLS) model was developed consisting of a wavelet-converted TLC image and 2,2-diphynyl-picrylhydrazyl free radical scavenging activity of 24 different preparations of P. bleo as the x- and y-variables, respectively. The quality of the constructed OPLS model (1 + 1 + 0) with one predictive and one orthogonal component was evaluated by internal and external validity tests. The validated model was then used to identify the contributing spot from the TLC plate that was then analyzed by GC-MS after trimethylsilyl derivatization. Glycerol and amine compounds were mainly found to contribute to the antioxidant activity of the sample. An alternative method to predict the antioxidant activity of a new sample of P. bleo leaves has been developed.
    Matched MeSH terms: Least-Squares Analysis
  16. Metabolomic analysis and biochemical changes in the urine and serum of streptozotocin-induced normal- and obese-diabetic rats
    Mediani A, Abas F, Maulidiani M, Abu Bakar Sajak A, Khatib A, Tan CP, et al.
    J Physiol Biochem, 2018 May 15.
    PMID: 29766441 DOI: 10.1007/s13105-018-0631-3
    Diabetes mellitus (DM) is a chronic disease that can affect metabolism of glucose and other metabolites. In this study, the normal- and obese-diabetic rats were compared to understand the diabetes disorders of type 1 and 2 diabetes mellitus. This was done by evaluating their urine metabolites using proton nuclear magnetic resonance (1H NMR)-based metabolomics and comparing with controls at different time points, considering the induction periods of obesity and diabetes. The biochemical parameters of the serum were also investigated. The obese-diabetic model was developed by feeding the rats a high-fat diet and inducing diabetic conditions with a low dose of streptozotocin (STZ) (25 mg/kg bw). However, the normal rats were induced by a high dose of STZ (55 mg/kg bw). A partial least squares discriminant analysis (PLS-DA) model showed the biomarkers of both DM types compared to control. The synthesis and degradation of ketone bodies, tricarboxylic (TCA) cycles, and amino acid pathways were the ones most involved in the variation with the highest impact. The diabetic groups also exhibited a noticeable increase in the plasma glucose level and lipid profile disorders compared to the control. There was also an increase in the plasma cholesterol and low-density lipoprotein (LDL) levels and a decline in the high-density lipoprotein (HDL) of diabetic rats. The normal-diabetic rats exhibited the highest effect of all parameters compared to the obese-diabetic rats in the advancement of the DM period. This finding can build a platform to understand the metabolic and biochemical complications of both types of DM and can generate ideas for finding targeted drugs.
    Matched MeSH terms: Least-Squares Analysis
  17. Fulltext NMR-Based Metabolomics Profiling for Radical Scavenging and Anti-Aging Properties of Selected Herbs
    Hussin M, Abdul Hamid A, Abas F, Ramli NS, Jaafar AH, Roowi S, et al.
    Molecules, 2019 Sep 03;24(17).
    PMID: 31484470 DOI: 10.3390/molecules24173208
    Herbs that are usually recognized as medicinal plants are well known for their therapeutic effects and are traditionally used to treat numerous diseases, including aging. This study aimed to evaluate the metabolite variations among six selected herbs namely Curcurmalonga, Oenanthejavanica, Vitex negundo, Plucheaindica, Cosmoscaudatus and Persicariaminus using proton nuclear magnetic resonance (1H-NMR) coupled with multivariate data analysis (MVDA). The free radical scavenging activity of the extract was measured by 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2-azinobis(3-ethyl-benzothiazoline-6-sulfonic acid) (ABTS) and oxygen radical absorbance capacity (ORAC) assay. The anti-aging property was characterized by anti-elastase and anti-collagenase inhibitory activities. The results revealed that P. minus showed the highest radical scavenging activities and anti-aging properties. The partial least squares (PLS) biplot indicated the presence of potent metabolites in P. minus such as quercetin, quercetin-3-O-rhamnoside (quercitrin), myricetin derivatives, catechin, isorhamnetin, astragalin and apigenin. It can be concluded that P. minus can be considered as a potential source for an anti-aging ingredient and also a good free radical eradicator. Therefore, P. minus could be used in future development in anti-aging researches and medicinal ingredient preparations.
    Matched MeSH terms: Least-Squares Analysis
  18. Discrimination of Malaysian stingless bee honey from different entomological origins based on physicochemical properties and volatile compound profiles using chemometrics and machine learning
    Sharin SN, Sani MSA, Jaafar MA, Yuswan MH, Kassim NK, Manaf YN, et al.
    Food Chem, 2021 Jun 01;346:128654.
    PMID: 33461823 DOI: 10.1016/j.foodchem.2020.128654
    Identification of honey origin based on specific chemical markers is important for honey authentication. This study is aimed to differentiate Malaysian stingless bee honey from different entomological origins (Heterotrigona bakeri, Geniotrigona thoracica and Tetrigona binghami) based on physicochemical properties (pH, moisture content, ash, total soluble solid and electrical conductivity) and volatile compound profiles. The discrimination pattern of 75 honey samples was observed using Principal Component Analysis (PCA), Hierarchical Clustering Analysis (HCA), Partial Least Square-Discriminant Analysis (PLS-DA), and Support Vector Machine (SVM). The profiles of H. bakeri and G. thoracica honey were close to each other, but clearly separated from T. binghami honey, consistent with their phylogenetic relationship. T. binghami honey is marked by significantly higher electrical conductivity, moisture and ash content, and high abundance of 2,6,6-trimethyl-1-cyclohexene-1-carboxaldehyde, 2,6,6-trimethyl-1-cyclohexene-1-acetaldehyde and ethyl 2-(5-methyl-5-vinyltetrahydrofuran-2-yl)propan-2-yl carbonate. Copaene was proposed as chemical marker for G. thoracica honey. The potential of different parameters that aid in honey authentication was highlighted.
    Matched MeSH terms: Least-Squares Analysis
  19. Fulltext The Influence of Person-Environment Fit on the Turnover Intention of Nurses in Jordan: The Moderating Effect of Psychological Empowerment
    Amarneh S, Raza A, Matloob S, Alharbi RK, Abbasi MA
    Nurs Res Pract, 2021;2021:6688603.
    PMID: 33815841 DOI: 10.1155/2021/6688603
    There is an acute shortage of nurses worldwide, including in Jordan. The nursing shortage is considered to be a crucial and complex challenge across healthcare systems and has stretched to a warning threshold. High turnover among nurses in Jordan is an enduring problem and is believed to be the foremost cause of the nurse shortage. The purpose of this study was to investigate the multidimensional impact of the person-environment (P-E) fit on the job satisfaction (JS) and turnover intention (TI) of registered nurses. The moderating effect of psychological empowerment (PE) on the relationship between JS and TI was also investigated. Based on a quantitative research design, data were collected purposively from 383 registered nurses working at private Jordanian hospitals through self-administered structured questionnaires. Statistical Package for Social Sciences (SPSS) 25 and Smart Partial Least Squares (PLS) 3.2.8 were used to analyze the statistical data. The results showed that there is a significant relationship between person-job fit (P-J fit), person-supervisor fit (P-S fit), and JS. However, this study found an insignificant relationship between person-organization fit (P-O fit) and JS. Moreover, PE was also significantly moderate between JS and TI of nurses. This study offers an important policy intervention that helps healthcare organizations to understand the enduring issue of nurse turnover. Additionally, policy recommendations to mitigate nurse turnover in Jordan are outlined.
    Matched MeSH terms: Least-Squares Analysis
  20. Fulltext Urine Untargeted Metabolomic Profiling Is Associated with the Dietary Pattern of Successful Aging among Malaysian Elderly
    Nik Mohd Fakhruddin NNI, Shahar S, Ismail IS, Ahmad Azam A, Rajab NF
    Nutrients, 2020 Sep 23;12(10).
    PMID: 32977370 DOI: 10.3390/nu12102900
    Food intake biomarkers (FIBs) can reflect the intake of specific foods or dietary patterns (DP). DP for successful aging (SA) has been widely studied. However, the relationship between SA and DP characterized by FIBs still needs further exploration as the candidate markers are scarce. Thus, 1H-nuclear magnetic resonance (1H-NMR)-based urine metabolomics profiling was conducted to identify potential metabolites which can act as specific markers representing DP for SA. Urine sample of nine subjects from each three aging groups, SA, usual aging (UA), and mild cognitive impairment (MCI), were analyzed using the 1H-NMR metabolomic approach. Principal components analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) were applied. The association between SA urinary metabolites and its DP was assessed using the Pearson's correlation analysis. The urine of SA subjects was characterized by the greater excretion of citrate, taurine, hypotaurine, serotonin, and melatonin as compared to UA and MCI. These urinary metabolites were associated with alteration in "taurine and hypotaurine metabolism" and "tryptophan metabolism" in SA elderly. Urinary serotonin (r = 0.48, p < 0.05) and melatonin (r = 0.47, p < 0.05) were associated with oat intake. These findings demonstrate that a metabolomic approach may be useful for correlating DP with SA urinary metabolites and for further understanding of SA development.
    Matched MeSH terms: Least-Squares Analysis
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