Displaying publications 1 - 20 of 266 in total

Abstract:
Sort:
  1. A Razak NF, Abd Karim RH, Jamal JA, Said MM
    J Pharm Bioallied Sci, 2020 Nov;12(Suppl 2):S752-S757.
    PMID: 33828373 DOI: 10.4103/jpbs.JPBS_364_19
    Introduction: The appendage of "halal" to a product is not just a guarantee that the product is permitted for Muslims, but it has also become favorable lifestyle choice globally. However, the expansion of halal pharmaceutical market was hindered by lack of global halal standards for pharmaceutical ingredients and product integrity analytical methodology.

    Objective: This work aimed to explore the possibility of using Fourier-transform infrared (FTIR) spectroscopy and chemometrics to develop multivariate models to authenticate the "halal-ity" of pharmaceutical excipients with controversial halal status (e.g., magnesium stearate).

    Materials and Methods: The FTIR spectral fingerprints of the substance were used to build principal component analysis (PCA) models. The effects of different spectral pretreatment processes such as auto-scaling, baseline correction, standard normal variate (SNV), first, and second derivatives were evaluated. The optimization of the model performance was established to ensure the sensitivity, specificity, and accuracy of the predicted models.

    Results: Significant peaks corresponding to the properties of the compound were identified. For both bovine and plant-derived magnesium stearate, the peaks associated can be seen within the regions 2900cm-1 (C-H), 2800cm-1 (CH3), 1700cm-1 (C=O), and 1000-1300cm-1 (C-O). There was not much difference observed in the FTIR raw spectra of the samples from both sources. The quality and accuracy of the classification models by PCA and soft independent modeling classification analogy (SIMCA) have shown to improve using spectra optimized by first derivative followed by SNV smoothing.

    Conclusion: This rapid and cost-effective technique has the potential to be expanded as an authentication strategy for halal pharmaceuticals.

    Matched MeSH terms: Principal Component Analysis
  2. Abbas, F.M.A., Foroogh, B., Liong, M.T., Azhar, M.E.
    MyJurnal
    Four types of soft dates (SD), three types of semi-dried dates (SDD) and one type of dried dates (DD) were used in this study. The antioxidant activities were assessed using TEAC method (ABTS assay) and the ferric reducing/antioxidant power method (FRAP assay), while total phenolic content (TPC) and total flavonoid content (TFC) were measured using Folin-Ciocalteau and aluminum chloride colorimetric methods. Multivariate analysis of variance (MANOVA), discriminant analysis (DA) and principal component analysis (PCA) were used to analyze the data. MANOVA showed a strong significant difference between the eight types of dates. DA identified the relative contribution of each parameter in distinguishing the dates. DA also identified two functions responsible for discriminating the dates and showed the difference between different types of dates. The first function distinguished DD from other types of dates, whilst the second function discriminated SD and SDD, affording 100% correct assignation. PCA identified only one component responsible for explaining 98.85% of the total variance in antioxidant data. It is suggested that the TEAC method and the quantitative determination of TPC and TFC was suitable for differentiation of dates and quality control.
    Matched MeSH terms: Principal Component Analysis
  3. Abdul Aziz Azdel, Khairil Wahidin Awang, Raja Nerina Raja Yusof, Salleh Mohd Radzi, Mohd Noor Ismawi Ismail
    MyJurnal
    The purpose of this study is to assess the determinants of psychological traits towards users’ technology experience specifically on Online Travel Agencies (OTA) via exploratory factor analysis (EFA). Working on these issues and after sequences of analyses to verify reliability and factor structure, the final 16 items of Technology Readiness 2.0 (TR2.0) with 4 items for each dimension (Optimism, Innovativeness, Discomfort, and Insecurity) have been congregated. Through an online survey, the technology readiness determinants were administered to 100 travelers at KLIA2 who have experienced on OTA. EFA using Principal Component Analysis with Varimax Rotation indicated 14 items, with 4 factors final solution with the following subscales: Innovativeness (4 items); Optimism (4 items); Discomfort (3 items); and Insecurities (3 items). All in all, only two items were removed from the original total of 16 items by the factor analysis based on the factor loading matrix for this final solution. This study basically plays an important role in contributing to the existing literature on the OTA users’ standpoint by using an approach which is very powerful to redefine the factors within Technology Readiness. This enhancement has reorganized the items according to their importance specifically towards new perspective which are OTA users in Malaysia setting.
    Matched MeSH terms: Principal Component Analysis
  4. Abdul Sani NF, Amir Hamzah AIZ, Abu Bakar ZH, Mohd Yusof YA, Makpol S, Wan Ngah WZ, et al.
    Cells, 2021 06 27;10(7).
    PMID: 34199148 DOI: 10.3390/cells10071611
    The mechanism of cognitive aging at the molecular level is complex and not well understood. Growing evidence suggests that cognitive differences might also be caused by ethnicity. Thus, this study aims to determine the gene expression changes associated with age-related cognitive decline among Malay adults in Malaysia. A cross-sectional study was conducted on 160 healthy Malay subjects, aged between 28 and 79, and recruited around Selangor and Klang Valley, Malaysia. Gene expression analysis was performed using a HumanHT-12v4.0 Expression BeadChip microarray kit. The top 20 differentially expressed genes at p < 0.05 and fold change (FC) = 1.2 showed that PAFAH1B3, HIST1H1E, KCNA3, TM7SF2, RGS1, and TGFBRAP1 were regulated with increased age. The gene set analysis suggests that the Malay adult's susceptibility to developing age-related cognitive decline might be due to the changes in gene expression patterns associated with inflammation, signal transduction, and metabolic pathway in the genetic network. It may, perhaps, have important implications for finding a biomarker for cognitive decline and offer molecular targets to achieve successful aging, mainly in the Malay population in Malaysia.
    Matched MeSH terms: Principal Component Analysis
  5. 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: Principal Component Analysis
  6. Abdul-Hamid NA, Abas F, Ismail IS, Tham CL, Maulidiani M, Mediani A, et al.
    Food Res Int, 2019 11;125:108565.
    PMID: 31554083 DOI: 10.1016/j.foodres.2019.108565
    Inflammation has been revealed to play a central role in the onset and progression of many illnesses. Nuclear magnetic resonance (NMR) based metabolomics method was adopted to evaluate the effects of Phoenix dactylifera seeds, in particular the Algerian date variety of Deglet on the metabolome of the LPS-IFN-γ-induced RAW 264.7 cells. Variations in the extracellular and intracellular profiles emphasized the differences in the presence of tyrosine, phenylalanine, alanine, proline, asparagine, isocitrate, inosine and lysine. Principal component analysis (PCA) revealed noticeable clustering patterns between the treated and induced RAW cells based on the metabolic profile of the extracellular metabolites. However, the effects of treatment on the intracellular metabolites appears to be less distinct as suggested by the PCA and heatmap analyses. A clear group segregation was observed for the intracellular metabolites from the treated and induced cells based on the orthogonal partial least squares-discriminant analysis (OPLS-DA) score plot. Likewise, 11 of the metabolites in the treated cells were significantly different from those in the induced groups, including amino acids and succinate. The enrichment analysis demonstrated that treatment with Deglet seed extracts interfered with the energy and of amino acids metabolism. Overall, the obtained data reinforced the possible application of Deglet seeds as a functional food with anti-inflammatory properties.
    Matched MeSH terms: Principal Component Analysis
  7. Abdul-Hamid NA, Mediani A, Maulidiani M, Shadid K, Ismail IS, Abas F, et al.
    J Food Sci Technol, 2018 Apr;55(4):1541-1551.
    PMID: 29606769 DOI: 10.1007/s13197-018-3073-6
    The aim of this study was to examine the variation in metabolite constituents of five commercial varieties of date fruits; Ajwa, Safawi and Ambar which originated from Madinah, the Iranian Bam and Tunisian Deglet Noor. The differences of metabolome were investigated using proton nuclear magnetic resonance (1H NMR) spectroscopy combined with multivariate data analysis (MVDA). Principal Component Analysis (PCA) revealed clear separation between the date varieties. The Tunisian Deglet Noor demonstrated distinct cluster from the rest of the palm date samples based on the metabolite composition as shown by the pattern observed in Hierarchical Clustering Analysis (HCA) and PCA. Deglet Noor exhibited a significant higher level of sucrose (δ 5.40) and fructose (δ 4.16) in comparison with the other four varieties which can be associated with the distinctive sweet taste of this variety. Dates originated from Madinah and Tunisia exhibited a contrast manner in the amount of xylose and moisture content. These two aspects may contribute towards the soft texture of Tunisian dates. All Madinah dates were found to contain phenolic compounds which were well established as great antioxidant and anti-inflammatory agent. Ajwa dates exerted greater effect in inhibiting the generation of nitric oxide (NO) from the stimulated RAW264.7 cells at 95.37% inhibition. Succinic acid was suggested to have the most significant correlation with the trend of NO inhibitory shown by the selected date palm varieties.
    Matched MeSH terms: Principal Component Analysis
  8. Abdullah MZ, Saat AB, Hamzah ZB
    Environ Monit Assess, 2012 Jun;184(6):3959-69.
    PMID: 21822578 DOI: 10.1007/s10661-011-2236-y
    Biomonitoring of multi-element atmospheric deposition using terrestrial moss is a well-established technique in Europe. Although the technique is widely known, there were very limited records of using this technique to study atmospheric air pollution in Malaysia. In this present study, the deposition of 11 trace metals surrounding the main petroleum refinery plant in Kerteh Terengganu (eastern part of peninsular Malaysia) has been evaluated using two local moss species, namely Hypnum plumaeforme and Taxithelium instratum as bioindicators. The study was also done by means of observing whether these metals are attributed to work related to oil exploration in this area. The moss samples have been collected at 30 sampling stations in the vicinity of the petrochemical industrial area covering up to 15 km to the south, north, and west in radius. The contents of heavy metal in moss samples were analyzed by energy dispersive x-ray fluorescence technique. Distribution of heavy metal content in all mosses is portrayed using Surfer software. Areas of the highest level of contaminations are highlighted. The results obtained using the principal components analysis revealed that the elements can be grouped into three different components that indirectly reflected three different sources namely anthropogenic factor, vegetation factor, and natural sources (soil dust or substrate) factor. Heavy metals deposited mostly in the distance after 9 km onward to the western part (the average direction of wind blow). V, Cr, Cu, and Hg are believed to have originated from local petrochemical-based industries operated around petroleum industrial area.
    Matched MeSH terms: Principal Component Analysis
  9. Abdullah P, Abdullah SMS, Jaafar O, Mahmud M, Khalik WMAWM
    Mar Pollut Bull, 2015 Dec 15;101(1):378-385.
    PMID: 26476861 DOI: 10.1016/j.marpolbul.2015.10.014
    Characterization of hydrochemistry changes in Johor Straits within 5 years of monitoring works was successfully carried out. Water quality data sets (27 stations and 19 parameters) collected in this area were interpreted subject to multivariate statistical analysis. Cluster analysis grouped all the stations into four clusters ((Dlink/Dmax) × 100<90) and two clusters ((Dlink/Dmax) × 100<80) for site and period similarities. Principal component analysis rendered six significant components (eigenvalue>1) that explained 82.6% of the total variance of the data set. Classification matrix of discriminant analysis assigned 88.9-92.6% and 83.3-100% correctness in spatial and temporal variability, respectively. Times series analysis then confirmed that only four parameters were not significant over time change. Therefore, it is imperative that the environmental impact of reclamation and dredging works, municipal or industrial discharge, marine aquaculture and shipping activities in this area be effectively controlled and managed.
    Matched MeSH terms: Principal Component Analysis
  10. Abu Bakar Sajak A, Azlan A, Abas F, Hamzah H
    Nutrients, 2021 Oct 12;13(10).
    PMID: 34684574 DOI: 10.3390/nu13103573
    An herbal mixture composed of lemon, apple cider, garlic, ginger and honey as a polyphenol-rich mixture (PRM) has been reported to contain hypolipidemic activity on human subjects and hyperlipidemic rats. However, the therapeutic effects of PRM on metabolites are not clearly understood. Therefore, this study aimed to provide new information on the causal impact of PRM on the endogenous metabolites, pathways and serum biochemistry. Serum samples of hyperlipidemic rats treated with PRM were subjected to biochemistry (lipid and liver profile) and hydroxymethylglutaryl-CoA enzyme reductase (HMG-CoA reductase) analyses. In contrast, the urine samples were subjected to urine metabolomics using 1H NMR. The serum biochemistry revealed that PRM at 500 mg/kg (PRM-H) managed to lower the total cholesterol level and low-density lipoprotein (LDL-C) (p < 0.05) and reduce the HMG-CoA reductase activity. The pathway analysis from urine metabolomics reveals that PRM-H altered 17 pathways, with the TCA cycle having the highest impact (0.26). Results also showed the relationship between the serum biochemistry of LDL-C and HMG-CoA reductase and urine metabolites (trimethylamine-N-oxide, dimethylglycine, allantoin and succinate). The study's findings demonstrated the potential of PRM at 500 mg/kg as an anti-hyperlipidemic by altering the TCA cycle, inhibiting HMG-CoA reductase and lowering the LDL-C in high cholesterol rats.
    Matched MeSH terms: Principal Component Analysis
  11. Adnan NH, Zakaria MP, Juahir H, Ali MM
    J Environ Sci (China), 2012;24(9):1600-8.
    PMID: 23520867
    The Langat River in Malaysia has been experiencing anthropogenic input from urban, rural and industrial activities for many years. Sewage contamination, possibly originating from the greater than three million inhabitants of the Langat River Basin, were examined. Sediment samples from 22 stations (SL01-SL22) along the Langat River were collected, extracted and analysed by GC-MS. Six different sterols were identified and quantified. The highest sterol concentration was found at station SL02 (618.29 ng/g dry weight), which situated in the Balak River whereas the other sediment samples ranged between 11.60 and 446.52 ng/g dry weight. Sterol ratios were used to identify sources, occurrence and partitioning of faecal matter in sediments and majority of the ratios clearly demonstrated that sewage contamination was occurring at most stations in the Langat River. A multivariate statistical analysis was used in conjunction with a combination of biomarkers to better understand the data that clearly separated the compounds. Most sediments of the Langat River were found to contain low to mid-range sewage contamination with some containing 'significant' levels of contamination. This is the first report on sewage pollution in the Langat River based on a combination of biomarker and multivariate statistical approaches that will establish a new standard for sewage detection using faecal sterols.
    Matched MeSH terms: Principal Component Analysis
  12. Agbolade O, Nazri A, Yaakob R, Ghani AA, Cheah YK
    BMC Bioinformatics, 2019 Dec 02;20(1):619.
    PMID: 31791234 DOI: 10.1186/s12859-019-3153-2
    BACKGROUND: Expression in H-sapiens plays a remarkable role when it comes to social communication. The identification of this expression by human beings is relatively easy and accurate. However, achieving the same result in 3D by machine remains a challenge in computer vision. This is due to the current challenges facing facial data acquisition in 3D; such as lack of homology and complex mathematical analysis for facial point digitization. This study proposes facial expression recognition in human with the application of Multi-points Warping for 3D facial landmark by building a template mesh as a reference object. This template mesh is thereby applied to each of the target mesh on Stirling/ESRC and Bosphorus datasets. The semi-landmarks are allowed to slide along tangents to the curves and surfaces until the bending energy between a template and a target form is minimal and localization error is assessed using Procrustes ANOVA. By using Principal Component Analysis (PCA) for feature selection, classification is done using Linear Discriminant Analysis (LDA).

    RESULT: The localization error is validated on the two datasets with superior performance over the state-of-the-art methods and variation in the expression is visualized using Principal Components (PCs). The deformations show various expression regions in the faces. The results indicate that Sad expression has the lowest recognition accuracy on both datasets. The classifier achieved a recognition accuracy of 99.58 and 99.32% on Stirling/ESRC and Bosphorus, respectively.

    CONCLUSION: The results demonstrate that the method is robust and in agreement with the state-of-the-art results.

    Matched MeSH terms: Principal Component Analysis
  13. Agbolade O, Nazri A, Yaakob R, Ghani AA, Cheah YK
    PLoS One, 2020;15(4):e0228402.
    PMID: 32271782 DOI: 10.1371/journal.pone.0228402
    BACKGROUND: The application of three-dimensional scan models offers a useful resource for studying craniofacial variation. The complex mathematical analysis for facial point acquisition in three-dimensional models has made many craniofacial assessments laborious.

    METHOD: This study investigates three-dimensional (3D) soft-tissue craniofacial variation, with relation to ethnicity, sex and age variables in British and Irish white Europeans. This utilizes a geometric morphometric approach on a subsampled dataset comprising 292 scans, taken from a Liverpool-York Head Model database. Shape variation and analysis of each variable are tested using 20 anchor anatomical landmarks and 480 sliding semi-landmarks.

    RESULTS: Significant ethnicity, sex, and age differences are observed for measurement covering major aspects of the craniofacial shape. The ethnicity shows subtle significant differences compared to sex and age; even though it presents the lowest classification accuracy. The magnitude of dimorphism in sex is revealed in the facial, nasal and crania measurement. Significant shape differences are also seen at each age group, with some distinct dimorphic features present in the age groups.

    CONCLUSIONS: The patterns of shape variation show that white British individuals have a more rounded head shape, whereas white Irish individuals have a narrower head shape. White British persons also demonstrate higher classification accuracy. Regarding sex patterns, males are relatively larger than females, especially in the mouth and nasal regions. Females presented with higher classification accuracy than males. The differences in the chin, mouth, nose, crania, and forehead emerge from different growth rates between the groups. Classification accuracy is best for children and senior adult age groups.

    Matched MeSH terms: Principal Component Analysis
  14. Ahmad Azam A, Ismail IS, Kumari Y, Shaikh MF, Abas F, Shaari K
    PLoS One, 2020;15(9):e0238503.
    PMID: 32925968 DOI: 10.1371/journal.pone.0238503
    Clinacanthus nutans (CN) (Acanthaceae) is well-known for its anti-inflammatory properties among Asian communities; however, there are currently no data specifically focused on the anti-inflammatory effects of CN on the brain tissue. Neuroinflammation is a common consequence of toxin intrusion to any part of the central nervous system (CNS). As an innate immune response, the CNS may react through both protective and/or toxic actions due to the activation of neuron cells producing pro- and/or anti-inflammatory cytokines in the brain. The unresolved activation of the inflammatory cytokines' response is associated with the pathogenesis of neurological disorders. The present study aimed to decipher the metabolic mechanism on the effects of 14 days oral treatment with CN aqueous extract in induced-lipopolysaccharides (LPS) rats through 1H NMR spectroscopic biomarker profiling of the brain tissue and the related cytokines. Based on the principal component analysis (PCA) of the nuclear magnetic resonance (NMR) spectral data, twenty-one metabolites in the brain tissue were profiled as biomarkers for the LPS (10 μL)-induced neuroinflammation following intracerebroventricular injection. Among the twenty-one biomarkers in the neuroinflammed rats, CN treatment of 1000 and 500 mg/kg BW successfully altered lactate, pyruvate, phosphorylcholine, glutamine, and α-ketoglutarate when compared to the negative control. Likewise, statistical isolinear multiple component analysis (SIMCA) showed that treatments by CN and the positive control drug, dextromethorphan (DXM, 5 mg/kg BW), have anti-neuroinflammatory potential. A moderate correlation, in the orthogonal partial least squares (OPLS) regression model, was found between the spectral metabolite profile and the cytokine levels. The current study revealed the existence of high levels of pro-inflammatory cytokines, namely IL-1α, IL-1β, and TNF-α in LPS-induced rats. Both CN dose treatments lowered IL-1β significantly better than DXM Interestingly, DXM and CN treatments both exhibited the upregulation of the anti-inflammatory cytokines IL-2 and 4. However, DXM has an advantage over CN in that the former also increased the expression of IL-10 of anti-inflammatory cytokines. In this study, a metabolomics approach was successfully applied to discover the mechanistic role of CN in controlling the neuroinflammatory conditions through the modulation of complex metabolite interactions in the rat brain.
    Matched MeSH terms: Principal Component Analysis
  15. Ahmad F, Hanafi MM, Hakim MA, Rafii MY, Arolu IW, Akmar Abdullah SN
    PLoS One, 2015;10(9):e0138246.
    PMID: 26393807 DOI: 10.1371/journal.pone.0138246
    Coloured rice genotypes have greater nutritious value and consumer demand for these varieties is now greater than ever. The documentation of these genotypes is important for the improvement of the rice plant. In this study, 42 coloured rice genotypes were selected for determination of their genetic divergence using 25 simple sequence repeat (SSR) primers and 15 agro-morphological traits. Twenty-one out of the 25 SSR primers showed distinct, reproducible polymorphism. A dendrogram constructed using the SSR primers clustered the 42 coloured rice genotypes into 7 groups. Further, principle component analysis showed 75.28% of total variations were explained by the first-three components. All agro-morphological traits showed significant difference at the (p≤0.05) and (p≤0.01) levels. From the dendrogram constructed using the agro-morphological traits, all the genotypes were clustered into four distinct groups. Pearson's correlation coefficient showed that among the 15 agro-morphological traits, the yield contributing factor had positive correlation with the number of tillers, number of panicles, and panicle length. The heritability of the 15 traits ranged from 17.68 to 99.69%. Yield per plant and harvest index showed the highest value for both heritability and genetic advance. The information on the molecular and agro-morphological traits can be used in rice breeding programmes to improve nutritional value and produce higher yields.
    Matched MeSH terms: Principal Component Analysis
  16. Ahmad R, Lim CK, Marzuki NF, Goh YK, Azizan KA, Goh YK, et al.
    Molecules, 2020 Dec 16;25(24).
    PMID: 33339375 DOI: 10.3390/molecules25245965
    In solving the issue of basal stem rot diseases caused by Ganoderma, an investigation of Scytalidium parasiticum as a biological control agent that suppresses Ganoderma infection has gained our interest, as it is more environmentally friendly. Recently, the fungal co-cultivation has emerged as a promising method to discover novel antimicrobial metabolites. In this study, an established technique of co-culturing Scytalidium parasiticum and Ganoderma boninense was applied to produce and induce metabolites that have antifungal activity against G. boninense. The crude extract from the co-culture media was applied to a High Performance Liquid Chromatography (HPLC) preparative column to isolate the bioactive compounds, which were tested against G. boninense. The fractions that showed inhibition against G. boninense were sent for a Liquid Chromatography-Time of Flight-Mass Spectrometry (LC-TOF-MS) analysis to further identify the compounds that were responsible for the microbicidal activity. Interestingly, we found that eudistomin I, naringenin 7-O-beta-D-glucoside and penipanoid A, which were present in different abundances in all the active fractions, except in the control, could be the antimicrobial metabolites. In addition, the abundance of fatty acids, such as oleic acid and stearamide in the active fraction, also enhanced the antimicrobial activity. This comprehensive metabolomics study could be used as the basis for isolating biocontrol compounds to be applied in oil palm fields to combat a Ganoderma infection.
    Matched MeSH terms: Principal Component Analysis
  17. Ahmadi K, Reidpath DD, Allotey P, Hassali MAA
    BMC Med Educ, 2016 May 30;16:155.
    PMID: 27240562 DOI: 10.1186/s12909-016-0676-3
    BACKGROUND: The attitudes of healthcare professionals towards HIV positive patients and high risk groups are central to the quality of care and therefore to the management of HIV/AIDS related stigma in health settings. Extant HIV/AIDS stigma scales that measure stigmatising attitudes towards people living with HIV/AIDS have been developed using scaling techniques such as principal component analysis. This approach has resulted in instruments that are often long. Mokken scale analysis is a nonparametric hierarchical scaling technique that can be used to develop unidimensional cumulative scales. This technique is advantageous over the other approaches; as the scales are usually shorter, while retaining acceptable psychometric properties. Moreover, Mokken scales also make no distributional assumptions about the underlying data, other than that the data are capable of being ordered by item and by person. In this study we aimed at developing a precise and concise measure of HIV/AIDS related stigma among health care professionals, using Mokken scale analysis.
    METHODS: We carried out a cross sectional survey of healthcare students at the Monash University campuses in Malaysia and Australia. The survey consisted of demographic questions and an initial item pool of twenty five potential questions for inclusion in an HIV stigma scale.
    RESULTS: We analysed the data using the mokken package in the R statistical environment providing a 9-item scale with high reliability, validity and acceptable psychometric properties, measuring and ranking the HIV/AIDS related stigmatising attitudes.
    CONCLUSION: Mokken scaling procedure not only produced a comprehensive hierarchical scale that could accurately order a person along HIV/AIDS stigmatising attitude, but also demonstrated a unidimensional and reliable measurement tool which could be used in future studies. The principal component analysis confirmed the accuracy of the Mokken scale analysis in correctly detecting the unidimensionality of this scale. We recommend future works to study the generalisability of this scale in a new population.
    Matched MeSH terms: Principal Component Analysis
  18. Ahmadian M, Samah AA, Redzuan M, Emby Z
    Glob J Health Sci, 2012 Jan 01;4(1):42-56.
    PMID: 22980116 DOI: 10.5539/gjhs.v4n1p42
    BACKGROUND: Although significant consideration has been devoted to women participation in breast cancer prevention programs, our understanding about the psychosocial factors which influence participation remains incomplete.

    METHOD: The study applied a quantitative approach based on the cross-sectional survey design and multistage cluster random sampling. A total of 400 women aged 35-69 years, were surveyed at 4 obstetric and gynecologic clinics affiliated to Tehran University of Medical Sciences in Tehran: the participation levels of 86 women who have had a mammogram were analyzed based on their self-efficacy, belief, social influence, and barriers concerning mammography utilization.

    RESULTS: Consistent with the study framework, in bivariate analysis, the higher level of women's participation in breast cancer prevention programs was significantly related to more positive belief about mammography (p< .05), greater social influence on mammography (p< .01) and fewer barriers to mammography (p< .01). Self efficacy (p= .114) was not significantly related to the higher level of participation.

    CONCLUSION: Results suggest that women's participation levels in breast cancer prevention programs might be associated with the specific psychosocial factors on breast cancer preventive behavior such as mammography screening.

    Matched MeSH terms: Principal Component Analysis
  19. Ajorlo M, Abdullah RB, Yusoff MK, Halim RA, Hanif AH, Willms WD, et al.
    Environ Monit Assess, 2013 Oct;185(10):8649-58.
    PMID: 23604787 DOI: 10.1007/s10661-013-3201-8
    This study investigates the applicability of multivariate statistical techniques including cluster analysis (CA), discriminant analysis (DA), and factor analysis (FA) for the assessment of seasonal variations in the surface water quality of tropical pastures. The study was carried out in the TPU catchment, Kuala Lumpur, Malaysia. The dataset consisted of 1-year monitoring of 14 parameters at six sampling sites. The CA yielded two groups of similarity between the sampling sites, i.e., less polluted (LP) and moderately polluted (MP) at temporal scale. Fecal coliform (FC), NO3, DO, and pH were significantly related to the stream grouping in the dry season, whereas NH3, BOD, Escherichia coli, and FC were significantly related to the stream grouping in the rainy season. The best predictors for distinguishing clusters in temporal scale were FC, NH3, and E. coli, respectively. FC, E. coli, and BOD with strong positive loadings were introduced as the first varifactors in the dry season which indicates the biological source of variability. EC with a strong positive loading and DO with a strong negative loading were introduced as the first varifactors in the rainy season, which represents the physiochemical source of variability. Multivariate statistical techniques were effective analytical techniques for classification and processing of large datasets of water quality and the identification of major sources of water pollution in tropical pastures.
    Matched MeSH terms: Principal Component Analysis
  20. Aketarawong N, Isasawin S, Thanaphum S
    BMC Genet, 2014;15:70.
    PMID: 24929425 DOI: 10.1186/1471-2156-15-70
    Bactrocera dorsalis s.s. (Hendel) and B. papayae Drew & Hancock, are invasive pests belonging to the B. dorsalis complex. Their species status, based on morphology, is sometimes arguable. Consequently, the existence of cryptic species and/or population isolation may decrease the effectiveness of the sterile insect technique (SIT) due to an unknown degree of sexual isolation between released sterile flies and wild counterparts. To evaluate the genetic relationship and current demography in wild populations for guiding the application of area-wide integrated pest management using SIT, seven microsatellite-derived markers from B. dorsalis s.s. and another five from B. papayae were used for surveying intra- and inter-specific variation, population structure, and recent migration among sympatric and allopatric populations of the two morphological forms across Southern Thailand and West Malaysia.
    Matched MeSH terms: Principal Component Analysis
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links