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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
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
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
A simple approach for rapid detection and quantification of adulterants in stingless bees (Heterotrigona itama) honey

Se KW, Ghoshal SK, Wahab RA, Ibrahim RKR, Lani MN

Food Res Int, 2018 03;105:453-460.
PMID: 29433236 DOI: 10.1016/j.foodres.2017.11.012

In this study, we propose an easy approach by combining the Fourier transform infrared and attenuated total reflectance (FTIR-ATR) spectroscopy together with chemometrics analysis for rapid detection and accurate quantification of five adulterants such as fructose, glucose, sucrose, corn syrup and cane sugar in stingless bees (Heterotrigona itama) honey harvested in Malaysia. Adulterants were classified using principal component analysis and soft independent modeling class analogy, where the first derivative of the spectra in the wavenumber range of 1180-750cm-1 was utilized. The protocol could satisfactorily discriminate the stingless bees honey samples that were adulterated with the concentrations of corn syrup above 8% (w/w) and cane sugar over 2% (w/w). Feasibility of integrating FTIR-ATR with chemometrics for precise quantification of the five adulterants was affirmed using partial least square regression (PLSR) analysis. The study found that optimal PLSR analysis achieved standard error of calibrations and standard error of predictions within an acceptable range of 0.686-1.087% and 0.581-1.489%, respectively, indicating good predictive capability. Hence, the method developed here for detecting and quantifying adulteration in H. itama honey samples is accurate and rapid, requiring only 7-8min to complete as compared to 3h for the standard method, AOAC method 998.12.

Matched MeSH terms: Least-Squares Analysis
Fulltext Metabolite profiling of endophytic Streptomyces spp. and its antiplasmodial potential

Ahmad SJ, Mohamad Zin N, Mazlan NW, Baharum SN, Baba MS, Lau YL

PeerJ, 2021;9:e10816.
PMID: 33777509 DOI: 10.7717/peerj.10816

Background: Antiplasmodial drug discovery is significant especially from natural sources such as plant bacteria. This research aimed to determine antiplasmodial metabolites of Streptomyces spp. against Plasmodium falciparum 3D7 by using a metabolomics approach.
Methods: Streptomyces strains' growth curves, namely SUK 12 and SUK 48, were measured and P. falciparum 3D7 IC50 values were calculated. Metabolomics analysis was conducted on both strains' mid-exponential and stationary phase extracts.
Results: The most successful antiplasmodial activity of SUK 12 and SUK 48 extracts shown to be at the stationary phase with IC50 values of 0.8168 ng/mL and 0.1963 ng/mL, respectively. In contrast, the IC50 value of chloroquine diphosphate (CQ) for antiplasmodial activity was 0.2812 ng/mL. The univariate analysis revealed that 854 metabolites and 14, 44 and three metabolites showed significant differences in terms of strain, fermentation phase, and their interactions. Orthogonal partial least square-discriminant analysis and S-loading plot putatively identified pavettine, aurantioclavine, and 4-butyldiphenylmethane as significant outliers from the stationary phase of SUK 48. For potential isolation, metabolomics approach may be used as a preliminary approach to rapidly track and identify the presence of antimalarial metabolites before any isolation and purification can be done.

Matched MeSH terms: Least-Squares Analysis
Fulltext Smart technology for healthcare: Exploring the antecedents of adoption intention of healthcare wearable technology

Chau KY, Lam MHS, Cheung ML, Tso EKH, Flint SW, Broom DR, et al.

Health Psychol Res, 2019 Mar 11;7(1):8099.
PMID: 31583292 DOI: 10.4081/hpr.2019.8099

Technological advancement and personalized health information has led to an increase in people using and responding to wearable technology in the last decade. These changes are often perceived to be beneficial, providing greater information and insights about health for users, organizations and healthcare and government. However, to date, understanding the antecedents of its adoption is limited. Seeking to address this gap, this cross-sectional study examined what factors influence users' adoption intention of healthcare wearable technology. We used self-administrated online survey to explore adoption intentions of healthcare wearable devices in 171 adults residing in Hong Kong. We analyzed the data by Partial least squares - structural equation modelling (PLS-SEM). The results reveal that perceived convenience and perceived irreplaceability are key predictors of perceived usefulness, which in turn strengthens users' adoption intention. Additionally, the results also reveal that health belief is one of the key predictors of adoption intention. This paper contributes to the extant literature by providing understanding of how to strengthen users' intention to adopt healthcare wearable technology. This includes the strengthening of perceived convenience and perceived irreplaceability to enhance the perceived usefulness, incorporating the extensive communication in the area of healthcare messages, which is useful in strengthening consumers' adoption intention in healthcare wearable technology.

Matched MeSH terms: Least-Squares Analysis
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
Fulltext UV-visible chemometrics approach for the determination of selected adulterants in claimed premixed coffee

Muhammad Zul Fayyadh Azizo Rahman, Chong, Hui Wen, Lim, Vuanghao

Malaysian Journal of Medicine and Health Sciences, 2018;14(102):1-6.
MyJurnal

Adulterated premixed coffees have turned into an issue in Malaysia lately and have caught the eye of the authorities due to death reports linked to these products. The major cause of this issue is reported that these premixed coffees have passed food inspection test and eventually released to the market for public consumption. These coffees were claimed to be spiked with several sexual enhancers like sildenafil, tadalafil, and vardenafill, which are common drugs used to treat erectile dysfunction. Methods: Chemometrics approach using UV-Vis spectroscopy was developed to detect the selected sexual enhancer drugs found in commercial coffees by employing SIMCA-P software for the multivariate statistical analysis. Seven brands of coffee samples were purchased from local stores, and 30 sachets each were tested, hence totalling to 210 samples. Each sample was named H, J, G, W, N, T, and K, respectively. Results: Three multivariate models were generated, namely principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), and partial least squares discriminant analysis (PLS-DA). OPLS-DA was selected as the best model for the overall results as it displayed minimal discriminate. Sildenafil, tadalafil, and vardenafil were detected in sample H, while vardenafil in brand J, and none in samples G, W, N, T, and K. Conclusion: OPLS-DA analysis showed discrimination for the sexual enhancer drugs in two brands of premixed coffee. The UV-Vis spectroscopy-based chemometrics method proved to be reliable and efficient in determining the selected drugs, as well as in saving time and cost.

Matched MeSH terms: Least-Squares Analysis
Fulltext Patients' perception of the information security management in health centers: the role of organizational and human factors

Peikari HR, T R, Shah MH, Lo MC

BMC Med Inform Decis Mak, 2018 Nov 15;18(1):102.
PMID: 30442138 DOI: 10.1186/s12911-018-0681-z

BACKGROUND: Researchers paid little attention to understanding the association of organizational and human factors with patients' perceived security in the context of health organizations. This study aims to address numerous gaps in this context. Patients' perceptions about employees' training on security issues, monitoring on security issues, ethics, physical & technical protection and trust in hospitals were identified as organizational and human factors.
METHODS: After the development of 12 hypotheses, a quantitative, cross-sectional, self-administered survey method was applied to collect data in 9 hospitals in Iran. After the collection of 382 usable questionnaires, the partial least square structural modeling was applied to examine the hypotheses and it was found that 11 hypotheses were empirically supported.
RESULTS: The results suggest that patients' trust in hospitals can significantly predict their perceived security but no significant associations were found between patients' physical protection mechanisms in the hospital and their perceived information security in a hospital. We also found that patients' perceptions about the physical protection mechanism of a hospital can significantly predict their trust in hospitals which is a novel finding by this research.
CONCLUSIONS: The findings imply that hospitals should formulate policies to improve patients' perception about such factors, which ultimately lead to their perceived security.

Matched MeSH terms: Least-Squares Analysis
Fulltext Effects of COVID-19 in E-learning on higher education institution students: the group comparison between male and female

Shahzad A, Hassan R, Aremu AY, Hussain A, Lodhi RN

Qual Quant, 2020 Aug 04.
PMID: 32836471 DOI: 10.1007/s11135-020-01028-z

In response to the emerging and ever solution to the COVID-19 outbreak. This study proposes a theoretical framework based on literature and model to determined E-learning portal success. The study compared males and females to E-learning portal usage. The study objective is to check the difference between male and female E-learning portals' accessibility among the students' perspective. The study included service quality, system quality, information quality, user satisfaction, system use, and E-learning portal success. The empirical data of 280 students participated from the different universities of Malaysia through google surveys analyzed using the Partial Least Squares Structural Equation Modelling. The study further divided the full model into two domains, which are female and male. In the male model, information quality and system quality have direct relationships with user satisfaction. Information quality also supported the relationship with system use. At the same time, there is a positive relationship between user satisfaction and E-learning portals. Likewise, in the female model, E-service quality and Information quality both are supported by system use and user satisfaction. Similarly, system quality has a positive relationship with user satisfaction, and user satisfaction has a positive relationship with E-learning portals. The study will be further helpful for the Malaysian universities policy-makers such as top management, ministry of higher education, Malaysian universities union in designing the policies and programs on E-learning Portal Success in the country. The findings of the study reveal that males and females have a different level of in terms of usage of towards E-learning portals in Malaysian Universities.

Matched MeSH terms: Least-Squares Analysis
Numerical optimization studies of cardiovascular-rotary blood pump interaction

Lim E, Dokos S, Salamonsen RF, Rosenfeldt FL, Ayre PJ, Lovell NH

Artif Organs, 2012 May;36(5):E110-24.
PMID: 22489799 DOI: 10.1111/j.1525-1594.2012.01449.x

A heart-pump interaction model has been developed based on animal experimental measurements obtained with a rotary blood pump in situ. Five canine experiments were performed to investigate the interaction between the cardiovascular system and the implantable rotary blood pump over a wide range of operating conditions, including variations in cardiac contractility and heart rate, systemic vascular resistance (SVR), and total blood volume (V(total) ). It was observed in our experiments that SVR decreased with increasing mean pump speed under the healthy condition, but was relatively constant during the speed ramp study under reduced cardiac contractility conditions. Furthermore, we also found a significant increase in pulmonary vascular resistance with increasing mean pump speed and decreasing total blood volume, despite a relatively constant SVR. Least squares parameter estimation methods were utilized to fit a subset of model parameters in order to achieve better agreement with the experimental data and to evaluate the robustness and validity of the model under various operating conditions. The fitted model produced reasonable agreement with the experimental measurements, both in terms of mean values and steady-state waveforms. In addition, all the optimized parameters were within physiological limits.

Matched MeSH terms: Least-Squares Analysis
New approach for sugarcane disease recognition through visible and near-infrared spectroscopy and a modified wavelength selection method using machine learning models

Ong P, Jian J, Li X, Zou C, Yin J, Ma G

Spectrochim Acta A Mol Biomol Spectrosc, 2023 Dec 05;302:123037.
PMID: 37356390 DOI: 10.1016/j.saa.2023.123037

The proliferation of pathogenic fungi in sugarcane crops poses a significant threat to agricultural productivity and economic sustainability. Early identification and management of sugarcane diseases are therefore crucial to mitigate the adverse impacts of these pathogens. In this study, visible and near-infrared spectroscopy (380-1400 nm) combined with a novel wavelength selection method, referred to as modified flower pollination algorithm (MFPA), was utilized for sugarcane disease recognition. The selected wavelengths were incorporated into machine learning models, including Naïve Bayes, random forest, and support vector machine (SVM). The developed simplified SVM model, which utilized the MFPA wavelength selection method yielded the best performances, achieving a precision value of 0.9753, a sensitivity value of 0.9259, a specificity value of 0.9524, and an accuracy of 0.9487. These results outperformed those obtained by other wavelength selection approaches, including the selectivity ratio, variable importance in projection, and the baseline method of the flower pollination algorithm.

Matched MeSH terms: Least-Squares Analysis
Visible and near-infrared spectroscopic determination of sugarcane chlorophyll content using a modified wavelength selection method for multivariate calibration

Ong P, Jian J, Li X, Yin J, Ma G

Spectrochim Acta A Mol Biomol Spectrosc, 2024 Jan 15;305:123477.
PMID: 37804706 DOI: 10.1016/j.saa.2023.123477

Spectroscopy in the visible and near-infrared region (Vis-NIR) region has proven to be an effective technique for quantifying the chlorophyll contents of plants, which serves as an important indicator of their photosynthetic rate and health status. However, the Vis-NIR spectroscopy analysis confronts a significant challenge concerning the existence of spectral variations and interferences induced by diverse factors. Hence, the selection of characteristic wavelengths plays a crucial role in Vis-NIR spectroscopy analysis. In this study, a novel wavelength selection approach known as the modified regression coefficient (MRC) selection method was introduced to enhance the diagnostic accuracy of chlorophyll content in sugarcane leaves. Experimental data comprising spectral reflectance measurements (220-1400 nm) were collected from sugarcane leaf samples at different growth stages, including seedling, tillering, and jointing, and the corresponding chlorophyll contents were measured. The proposed MRC method was employed to select optimal wavelengths for analysis, and subsequent partial least squares regression (PLSR) and Gaussian process regression (GPR) models were developed to establish the relationship between the selected wavelengths and the measured chlorophyll contents. In comparison to full-spectrum modelling and other commonly employed wavelength selection techniques, the proposed simplified MRC-GPR model, utilizing a subset of 291 selected wavelengths, demonstrated superior performance. The MRC-GPR model achieved higher coefficient of determination of 0.9665 and 0.8659, and lower root mean squared error of 1.7624 and 3.2029, for calibration set and prediction set, respectively. Results showed that the GPR model, a nonlinear regression approach, outperformed the PLSR model.

Matched MeSH terms: Least-Squares Analysis
Fulltext Predictors of COVID-19 Preventive Behavior Adoption Intention in Malaysia

Mat Dawi N, Namazi H, Maresova P

Front Psychol, 2021;12:616749.
PMID: 34093307 DOI: 10.3389/fpsyg.2021.616749

Preventive behavior adoption is the key to reduce the possibility of getting COVID-19 infection. This paper aims to examine the determinants of intention to adopt preventive behavior by incorporating perception of e-government information and services and perception of social media into the theory of reasoned action. A cross-sectional online survey was carried out among Malaysian residents. Four hundred four valid responses were obtained and used for data analysis. A partial least-square-based path analysis revealed direct effects of attitude and subjective norm in predicting intention to adopt preventive behavior. In addition, perception of e-government information and services and perception of social media were found to be significant predictors of attitude toward preventive behavior. The findings highlight the importance of digital platforms in improving people's attitudes toward preventive behavior and in turn contain the spread of the infectious disease.

Matched MeSH terms: Least-Squares Analysis
Fulltext Strategic public procurement regulatory compliance model with mediating effect of ethical behavior

Sarawa DI, Mas'ud A

Heliyon, 2020 Jan;6(1):e03132.
PMID: 32042941 DOI: 10.1016/j.heliyon.2019.e03132

The paper proposes and validates the strategic public procurement regulatory compliance model with mediation effect of ethical behavior. It expands the socio-economic theory of regulatory compliance to explore the mediating effect of ethical behavior on the influence of professionalism, familiarity, enforcement, resistance to political pressure and compliance with public procurement regulation. A quantitative research design was deployed using 125 procurement officers as a sample group. The data from the sample was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results validated the hypotheses for the strategic public procurement regulatory compliance model with mediation effect of ethical behavior. The study not only confirmed the earlier findings on the direct effects of professionalism, familiarity, enforcement, resistance to political pressure and ethical behavior on compliance, but also established the mediating effect of ethical behavior on compliance on all the predictors except resistance to political pressure. The study implied that ethical behavior of public procurement officers should be a strategic point of concern by both policymakers and professional bodies. Theoretically, the studyexpands thesocio-economic theory of regulatory compliance within the context of procurement literature through mediation effects of ethical behavior via structural analysis.

Matched MeSH terms: Least-Squares Analysis
Disposable E-Tongue for the Assessment of Water Quality in Fish Tanks

Chang CC, Saad B, Surif M, Ahmad MN, Md Shakaff AY

Sensors (Basel), 2008 Jun 01;8(6):3665-3677.
PMID: 27879900

A disposable screen-printed e-tongue based on sensor array and pattern recognition that is suitable for the assessment of water quality in fish tanks is described. The characteristics of sensors fabricated using two kinds of sensing materials, namely (i) lipids (referred to as Type 1), and (ii) alternative electroactive materials comprising liquid ion-exchangers and macrocyclic compounds (Type 2) were evaluated for their performance stability, sensitivity and reproducibility. The Type 2 e-tongue was found to have better sensing performance in terms of sensitivity and reproducibility and was thus used for application studies. By using a pattern recognition tool i.e. principal component analysis (PCA), the e-tongue was able to discriminate the changes in the water quality in tilapia and catfish tanks monitored over eight days. E-tongues coupled with partial least squares (PLS) was used for the quantitative analysis of nitrate and ammonium ions in catfish tank water and good agreement were found with the ion-chromatography method (relative error, ±1.04- 4.10 %).

Matched MeSH terms: Least-Squares Analysis
Fulltext The performance of robust modification of breusch-godfrey test in the presence of outliers

Lim, H. A., Midi, H.

Pertanika Journal of Science & Technology, 2014;22(1):81-93.
MyJurnal

Autocorrelation problem causes unduly effects on the variance of Ordinary Least Squares (OLS) estimates. Hence, it is very essential to detect the autocorrelation problem so that appropriate remedial measures can be taken. The Breusch-Godfrey (BG) test is the most popular and commonly used test for the detection of autocorrelation. Since this test is based on the OLS estimates, which are not robust, it is easily affected by outliers. In this paper, we propose a robust Breusch-Godfrey (MBG) test which is not easily affected by outliers. The results of the study indicate that the MBG test is more powerful than the BG test in the detection of autocorrelation problem.

Matched MeSH terms: Least-Squares Analysis
Fulltext Does It Matter Who Exhibits More Green Purchase Behavior of Cosmetic Products in Asian Culture? A Multi-Group Analysis Approach

Quoquab F, Jaini A, Mohammad J

Int J Environ Res Public Health, 2020 07 21;17(14).
PMID: 32708199 DOI: 10.3390/ijerph17145258

This study attempts to investigate the moderating effect of gender on value-belief-norm relationships. In addition, this study aims to investigate the factors that affect green purchase behavior of cosmetics products. Particularly, this study investigates the causal relationships between values and pro-environmental beliefs, pro-environmental beliefs and personal norms and personal norms and green purchase behavior. An online survey was carried out which yielded 240 usable responses among which 79 responses were obtained from males and 161 from females. Data were analyzed using structural equation modeling, partial least square (PLS-SEM) approach and multi-group analysis (MGA) technique. Results revealed that all direct relationships were supported by the data. It was also found that gender moderates the relationships between altruistic values and pro-environmental beliefs, pro-environmental beliefs and personal norms and personal norms and green purchase behavior. Nevertheless, gender did not moderate the link between hedonic value and pro-environmental beliefs. This study contributes to the existing literature by considering gender as a moderator, which is comparatively new in the green purchase behavior literature. In addition, this study examines few new linkages: more specifically, incorporating hedonic value in value-belief link and adapting value-belief-norm (VBN) theory in measuring consumers' green purchase behavior.

Matched MeSH terms: Least-Squares Analysis
Fulltext The determinants of total fertility rate in selected Asian countries: an empirical study using panel data

Asef Raiyan Hoque, Mohd Yusof Ibrahim, Mohammad Zahirul Hoque

Malaysian Journal of Medicine and Health Sciences, 2019;15(106):18-18.
MyJurnal

Introduction: In recent years, the variation in total fertility rate (TFR) has sparked public interest for demographic concerns on the global population shift towards an older age structure. This study aims to investigate the determi-nants of total fertility rate among Brunei, Indonesia, Malaysia and Philippines East Asian Growth Area (BIMP-EAGA) region. Methods: Our empirical study consists of data collected from the United Nations Development Report of the UNDP, World Development Indicators (WDI) of the World Bank and World Health Organization (WHO) report 2018. We investigated the socio-economic determinants of fertility rate by analyzing a panel data set consisting of 28 years from 1990-2017 of the four countries. A statistical and econometric software EViews version 10 (HIS Global Inc., Irvine, CA, USA) were used to run a Pearson’s Correlation and a multiple regression analysis by panel least squares method. To investigate the determinants of TFR we have selected five socio- economic factors, these are- Infant mortality rate (IMR), Gross National Income Per Capita, PPP (GNI), Human Development Index (HDI), percentage of population living in urban areas (URB) and lastly Female Labor Force Participation Rate (FLP). Results:Pearson’s correlation showed that a statistically significant negative relationship exists between TFR and the 3 vari-ables- GNI, URB and HDI. A statistically strong positive relationship exists between IMR and TFR. However, our results from the empirical multiple regression model indicates that there is a statistically significant negative relation-ship exists between TFR and two of the independent variables GNI and FLP. Conclusion: The results of present study showed that an increase in the national income and female labor participation rate in the workforce could result in a decrease in total fertility rate. These findings may have implications for countries national policy for planning, development and resource allocation.

Matched MeSH terms: Least-Squares Analysis
Fulltext Metabolic profiling of Lactococcus lactis under different culture conditions

Azizan KA, Baharum SN, Mohd Noor N

Molecules, 2012 Jul 03;17(7):8022-36.
PMID: 22759915 DOI: 10.3390/molecules17078022

Gas chromatography mass spectrometry (GC-MS) and headspace gas chromatography mass spectrometry (HS/GC-MS) were used to study metabolites produced by Lactococcus lactis subsp. cremoris MG1363 grown at a temperature of 30 °C with and without agitation at 150 rpm, and at 37 °C without agitation. It was observed that L. lactis produced more organic acids under agitation. Primary alcohols, aldehydes, ketones and polyols were identified as the corresponding trimethylsilyl (TMS) derivatives, whereas amino acids and organic acids, including fatty acids, were detected through methyl chloroformate derivatization. HS analysis indicated that branched-chain methyl aldehydes, including 2-methylbutanal, 3-methylbutanal, and 2-methylpropanal are degdradation products of isoleucine, leucine or valine. Multivariate analysis (MVA) using partial least squares discriminant analysis (PLS-DA) revealed the major differences between treatments were due to changes of amino acids and fermentation products.

Matched MeSH terms: Least-Squares Analysis

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