Displaying publications 161 - 180 of 271 in total

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  1. Application of third molar development and eruption models in estimating dental age in Malay sub-adults
    Mohd Yusof MY, Cauwels R, Deschepper E, Martens L
    J Forensic Leg Med, 2015 Aug;34:40-4.
    PMID: 26165657 DOI: 10.1016/j.jflm.2015.05.004
    The third molar development (TMD) has been widely utilized as one of the radiographic method for dental age estimation. By using the same radiograph of the same individual, third molar eruption (TME) information can be incorporated to the TMD regression model. This study aims to evaluate the performance of dental age estimation in individual method models and the combined model (TMD and TME) based on the classic regressions of multiple linear and principal component analysis. A sample of 705 digital panoramic radiographs of Malay sub-adults aged between 14.1 and 23.8 years was collected. The techniques described by Gleiser and Hunt (modified by Kohler) and Olze were employed to stage the TMD and TME, respectively. The data was divided to develop three respective models based on the two regressions of multiple linear and principal component analysis. The trained models were then validated on the test sample and the accuracy of age prediction was compared between each model. The coefficient of determination (R²) and root mean square error (RMSE) were calculated. In both genders, adjusted R² yielded an increment in the linear regressions of combined model as compared to the individual models. The overall decrease in RMSE was detected in combined model as compared to TMD (0.03-0.06) and TME (0.2-0.8). In principal component regression, low value of adjusted R(2) and high RMSE except in male were exhibited in combined model. Dental age estimation is better predicted using combined model in multiple linear regression models.
    Matched MeSH terms: Principal Component Analysis
  2. Fulltext Survival Rate and Transcriptional Response upon Infection with the Generalist Parasite Beauveria bassiana in a World-Wide Sample of Drosophila melanogaster
    Paparazzo F, Tellier A, Stephan W, Hutter S
    PLoS One, 2015;10(7):e0132129.
    PMID: 26154519 DOI: 10.1371/journal.pone.0132129
    The ability to cope with infection by a parasite is one of the major challenges for any host species and is a major driver of evolution. Parasite pressure differs between habitats. It is thought to be higher in tropical regions compared to temporal ones. We infected Drosophila melanogaster from two tropical (Malaysia and Zimbabwe) and two temperate populations (the Netherlands and North Carolina) with the generalist entomopathogenic fungus Beauveria bassiana to examine if adaptation to local parasite pressures led to differences in resistance. Contrary to previous findings we observed increased survival in temperate populations. This, however, is not due to increased resistance to infection per se, but rather the consequence of a higher general vigor of the temperate populations. We also assessed transcriptional response to infection within these flies eight and 24 hours after infection. Only few genes were induced at the earlier time point, most of which are involved in detoxification. In contrast, we identified more than 4,000 genes that changed their expression state after 24 hours. This response was generally conserved over all populations with only few genes being uniquely regulated in the temperate populations. We furthermore found that the American population was transcriptionally highly diverged from all other populations concerning basal levels of gene expression. This was particularly true for stress and immune response genes, which might be the genetic basis for their elevated vigor.
    Matched MeSH terms: Principal Component Analysis
  3. Health Risk Assessment of Heavy Metal in Urban Surface Soil (Klang District, Malaysia)
    Yuswir NS, Praveena SM, Aris AZ, Ismail SN, Hashim Z
    Bull Environ Contam Toxicol, 2015 Jul;95(1):80-9.
    PMID: 25904089 DOI: 10.1007/s00128-015-1544-2
    Urban environmental quality is vital to be investigated as the majority of people live in cities. However, given the continuous urbanization and industrialization in urban areas, heavy metals are continuously emitted into the terrestrial environment and pose a great threat to human. In this study, a total of 76 urban surface soil samples were collected in the Klang district (Malaysia), and analyzed for total and bioavailable heavy metal concentrations by inductively coupled plasma-optical emission spectrometry. Results showed that the concentrations of bioavailable heavy metals declined in the order of Al, Fe, Zn, Cu, Co, Cd, Pb, and Cr, and the concentrations of total heavy metals declined in the order of Fe, Al, Cu, Zn, Pb, Cr, Co, and Cd. Principal component analysis (PCA) showed that heavy metals could be grouped into three principal components, with PC1 containing Al and Fe, PC2 comprising Cd, Co, Cr, and Cu, and PC3 with only Zn. PCA results showed that PC1 may originate from natural sources, whereas PC2 and PC3 most likely originated from anthropogenic sources. Health risk assessment indicated that heavy metal contamination in the Klang district was below the acceptable threshold for carcinogenic and non-carcinogenic risks in adults, but above the acceptable threshold for carcinogenic and non-carcinogenic risks in children.
    Matched MeSH terms: Principal Component Analysis
  4. Molecular dynamics simulations and principal component analysis on human laforin mutation W32G and W32G/K87A
    Srikumar PS, Rohini K, Rajesh PK
    Protein J, 2014 Jun;33(3):289-95.
    PMID: 24770803 DOI: 10.1007/s10930-014-9561-2
    Mutations in human laforin lead to an autosomal neurodegenerative disorder Lafora disease. In N-terminal carbohydrate binding domain of laforin, two mutations W32G and K87A are reported as highly disease causing laforin mutants. Experimental studies reported that mutations are responsible for the abolishment of glycogen binding which is a critical function of laforin. Our current computational study focused on the role of conformational changes in human laforin structure due to existing single mutation W32G and prepared double mutation W32G/K87A related to loss of glycogen binding. We performed 10 ns molecular dynamics (MD) simulation studies in the Gromacs package for both mutations and analyzed the trajectories. From the results, the global properties like root mean square deviation, root mean square fluctuation, radius of gyration, solvent accessible surface area and hydrogen bonds showed structural changes in atomic level observed in W32G and W32G/K87A laforin mutants. The conformational change induced by mutants influenced the loss of the overall stability of the native laforin. Moreover, the change in overall motion of protein was analyzed by principal component analysis and results showed protein clusters expanded more than native and also change in direction in case of double mutant in conformational space. Overall, our report provides theoretical information on loss of structure-function relationship due to flexible nature of laforin mutants. In conclusion, comparative MD simulation studies support the experimental data on W32G and W32G/K87A related to the lafora disease mechanism on glycogen binding.
    Matched MeSH terms: Principal Component Analysis
  5. Geographical variation of skull morphology and its functional significances in the red-cheeked squirrel
    Endo H, Kimura J, Oshida T, Stafford BJ, Rerkamnuaychoke W, Nishida T, et al.
    J Vet Med Sci, 2003 Nov;65(11):1179-83.
    PMID: 14665745
    Skulls of the red-cheeked squirrel (Dremomys rufigenis) from various geographical locations: Malaysia (peninsular area), Vietnam (south district)-Laos, and Thailand (north district) were osteometrically examined. The skull size of the squirrels in the southern (Malaysia) population was fundamentally larger than that in the northern (Vietnam, Laos and Thailand) populations. The proportion indices indicated that the splanchnocranium was relatively longer in the Malaysia population, and that the interorbital space was narrower in Vietnam-Laos, and Thailand populations. We suggest that the long nose and laterally-oriented orbits in the skull may be better adapted for terrestrial-insectivorous life in the Malaysia population and the binocular sense facilitated by rostrally-oriented eyes contributes to the arboreal-fruit eating behavior in the two northern populations. The Malaysia population was clearly distinguished from the other populations by the principal component analysis. We suggest that the geographical barrier of the Isthmus of Kra influences the morphological variation of the skull among the squirrel populations.
    Matched MeSH terms: Principal Component Analysis
  6. The sources and ecological risk assessment of elemental pollution in sediment of Linggi estuary, Malaysia
    Elias MS, Ibrahim S, Samuding K, Rahman SA, Hashim A
    Mar Pollut Bull, 2018 Dec;137:646-655.
    PMID: 30503479 DOI: 10.1016/j.marpolbul.2018.11.006
    In this study, concentrations of heavy metals, rare earth elements (REEs), Uranium (U) and Thorium (Th) of the actinide group were determined from Linggi estuary sediment samples by neutron activation analysis (NAA) and inductive coupled plasma - mass spectrometry techniques. The geo-accumulation (Igeo) and ecological risk index (Ri) values were calculated to identify the quality status of Linggi estuary sediments. Results indicated Linggi estuary was polluted by arsenic (As), lead (Pb) and antimony (Sb). REEs, U and Th showed significant increase of concentration in Linggi estuary sediments. Ri of Linggi estuary was categorised as low to considerable ecological risk, which indicates no significant to moderate effect on the majority of the sediment-dwelling organisms. Correlation matrix and principal component analysis assessed pollution sources to be both natural and anthropogenic.
    Matched MeSH terms: Principal Component Analysis
  7. Applied chemometric approach in identification sources of air quality pattern in Selangor, Malaysia
    Ang KH
    Sains Malaysiana, 2018;47:471-479.
    In recent years, Malaysia has experienced quite a few number of chronic air pollution problems and it has become a
    major contributor to the deterioration of human health and ecosystems. This study aimed to assess the air quality data
    and identify the pattern of air pollution sources using chemometric analysis through hierarchical cluster analysis (HCA),
    discriminant analysis (DA), principal component analysis (PCA) and multiple linear regression analysis (MLR). The air
    quality data from January 2016 until December 2016 was obtained from the Department of Environment Malaysia. Air
    quality data from eight sampling stations in Selangor include the selected variables of nitrogen dioxide (NO2
    ), ozone (O3
    ),
    sulfur dioxide (SO2
    ), carbon monoxide (CO) and particulate matter (PM10). The HCA resulted in three clusters, namely low
    pollution source (LPS), moderate pollution source (MPS) and slightly high pollution source (SHPS). Meanwhile, DA resulted
    in two and four variables for the forward stepwise mode and the backward stepwise mode, respectively. Through PCA,
    it was identified that the main pollutants of LPS, MPS and SHPS came from industrial and vehicle emissions, agricultural
    systems, residential factors and natural emission sources. Among the three models yielded from the MLR analysis, it was
    found that SHPS is the most suitable model to be used for the prediction of Air Pollution Index. This study concluded that
    a clearer review and practical design of air quality monitoring network would be beneficial for better management of
    air pollution. The study also suggested that chemometric techniques have the ability to show significant information on
    spatial variability for large and complex air quality data.
    Matched MeSH terms: Principal Component Analysis
  8. 1H-NMR-based metabolomics to investigate the effects of Phoenix dactylifera seed extracts in LPS-IFN-γ-induced RAW 264.7 cells
    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
  9. Rapid identification of pork for halal authentication using the electronic nose and gas chromatography mass spectrometer with headspace analyzer
    Nurjuliana M, Che Man YB, Mat Hashim D, Mohamed AK
    Meat Sci, 2011 Aug;88(4):638-44.
    PMID: 21420795 DOI: 10.1016/j.meatsci.2011.02.022
    The volatile compounds of pork, other meats and meat products were studied using an electronic nose and gas chromatography mass spectrometer with headspace analyzer (GCMS-HS) for halal verification. The zNose™ was successfully employed for identification and differentiation of pork and pork sausages from beef, mutton and chicken meats and sausages which were achieved using a visual odor pattern called VaporPrint™, derived from the frequency of the surface acoustic wave (SAW) detector of the electronic nose. GCMS-HS was employed to separate and analyze the headspace gasses from samples into peaks corresponding to individual compounds for the purpose of identification. Principal component analysis (PCA) was applied for data interpretation. Analysis by PCA was able to cluster and discriminate pork from other types of meats and sausages. It was shown that PCA could provide a good separation of the samples with 67% of the total variance accounted by PC1.
    Matched MeSH terms: Principal Component Analysis
  10. 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: Principal Component Analysis
  11. Probing the characteristics and biofunctional effects of disease-affected cells and drug response via machine learning applications
    Mudali D, Jeevanandam J, Danquah MK
    Crit Rev Biotechnol, 2020 Nov;40(7):951-977.
    PMID: 32633615 DOI: 10.1080/07388551.2020.1789062
    Drug-induced transformations in disease characteristics at the cellular and molecular level offers the opportunity to predict and evaluate the efficacy of pharmaceutical ingredients whilst enabling the optimal design of new and improved drugs with enhanced pharmacokinetics and pharmacodynamics. Machine learning is a promising in-silico tool used to simulate cells with specific disease properties and to determine their response toward drug uptake. Differences in the properties of normal and infected cells, including biophysical, biochemical and physiological characteristics, plays a key role in developing fundamental cellular probing platforms for machine learning applications. Cellular features can be extracted periodically from both the drug treated, infected, and normal cells via image segmentations in order to probe dynamic differences in cell behavior. Cellular segmentation can be evaluated to reflect the levels of drug effect on a distinct cell or group of cells via probability scoring. This article provides an account for the use of machine learning methods to probe differences in the biophysical, biochemical and physiological characteristics of infected cells in response to pharmacokinetics uptake of drug ingredients for application in cancer, diabetes and neurodegenerative disease therapies.
    Matched MeSH terms: Principal Component Analysis
  12. Untargeted MS-based small metabolite identification from the plant leaves and stems of Impatiens balsamina
    Chua LS
    Plant Physiol Biochem, 2016 Sep;106:16-22.
    PMID: 27135814 DOI: 10.1016/j.plaphy.2016.04.040
    The identification of plant metabolites is very important for the understanding of plant physiology including plant growth, development and defense mechanism, particularly for herbal medicinal plants. The metabolite profile could possibly be used for future drug discovery since the pharmacological activities of the indigenous herbs have been proven for centuries. An untargeted mass spectrometric approach was used to identify metabolites from the leaves and stems of Impatiens balsamina using LC-DAD-MS/MS. The putative compounds are mostly from the groups of phenolic, organic and amino acids which are essential for plant growth and as intermediates for other compounds. Alanine appeared to be the main amino acid in the plant because many alanine derived metabolites were detected. There are also several secondary metabolites from the groups of benzopyrones, benzofuranones, naphthoquinones, alkaloids and flavonoids. The widely reported bioactive components such as kaempferol, quercetin and their glycosylated, lawsone and its derivatives were detected in this study. The results also revealed that aqueous methanol could extract flavonoids better than water, and mostly, flavonoids were detected from the leaf samples. The score plots of component analysis show that there is a minor variance in the metabolite profiles of water and aqueous methanolic extracts with 21.5 and 30.5% of the total variance for the first principal component at the positive and negative ion modes, respectively.
    Matched MeSH terms: Principal Component Analysis
  13. Habitual Dietary Patterns of Patients on Hemodialysis Indicate Nutritional Risk
    Sualeheen A, Khor BH, Balasubramanian GV, Sahathevan S, Ali MSM, Narayanan SS, et al.
    J Ren Nutr, 2020 07;30(4):322-332.
    PMID: 31767516 DOI: 10.1053/j.jrn.2019.09.010
    OBJECTIVE: This study aimed to (i) determine habitual dietary patterns of Malaysian patients on hemodialysis (HD) and (ii) examine their association with nutritional status.

    METHODS: An à posteriori approach examined 3-day dietary recalls of 382 multiethnic Malaysian patients on HD, leading to short-listing of 31 food groups. Dietary patterns were derived through principal component analysis. Sociodemographic and lifestyle characteristics together with nutritional parameters were examined for associations with specific dietary patterns.

    RESULTS: Four dietary patterns emerged, namely, "Home Food," "Eating Out (EO)-Rice," "EO-Sugar sweetened beverages," and "EO-Noodle." Younger patients, male gender, Malay, and patients with working status were more likely to follow "EO-Rice" and "EO-Sugar sweetened beverages" patterns, while Chinese patients were more likely to consume "EO-Noodle" pattern (all P values 

    Matched MeSH terms: Principal Component Analysis
  14. Fulltext Chemometrics of differentially expressed proteins from colorectal cancer patients
    Yeoh LC, Dharmaraj S, Gooi BH, Singh M, Gam LH
    World J Gastroenterol, 2011 Apr 28;17(16):2096-103.
    PMID: 21547128 DOI: 10.3748/wjg.v17.i16.2096
    To evaluate the usefulness of differentially expressed proteins from colorectal cancer (CRC) tissues for differentiating cancer and normal tissues.
    Matched MeSH terms: Principal Component Analysis
  15. Proteomic profiling of clinical and environmental strains of Pseudomonas aeruginosa
    Liew SM, Puthucheary SD, Rajasekaram G, Chai HC, Chua KH
    Mol Biol Rep, 2021 Mar;48(3):2325-2333.
    PMID: 33728559 DOI: 10.1007/s11033-021-06262-8
    Pseudomonas aeruginosa is a ubiquitous bacterium, which is able to change its physiological characteristics in response to different habitats. Environmental strains are presumably less pathogenic than clinical strains and whether or not the clinical strains originate from the environment or through inter-host transmission remains poorly understood. To minimize the risk of infection, a better understanding of proteomic profiling of P. aeruginosa is necessary for elucidating the correlation between environmental and clinical strains. Based on antimicrobial susceptibility and patterns of virulence, we selected 12 clinical and environmental strains: (i) environmental, (ii) multidrug resistant (MDR) clinical and (iii) susceptible clinical strains. Whole-cell protein was extracted from each strain and subjected to two-dimensional differential gel electrophoresis (2-D DIGE) and liquid chromatography tandem mass spectrometry quadrupole time-of-flight (LC-MS QTOF). All 12 strains were clustered into 3 distinct groups based on their variance in protein expression. A total of 526 matched spots were detected and four differentially expressed protein spots (p < 0.05) were identified and all differential spots were downregulated in MDR strain J3. Upregulation of chitin binding and BON domain proteins was present in the environmental and some MDR strains, whereas the clinical strains exhibited distinct proteomic profiles with increased expression of serine protein kinase and arginine/ornithine transport ATP-binding proteins. Significant difference in expression was observed between susceptible clinical and MDR strains, as well as susceptible clinical and environmental strains. Transition from an environmental saprophyte to a clinical strain could alter its physiological characteristics to further increase its adaptation.
    Matched MeSH terms: Principal Component Analysis
  16. Chemical composition of the essential oils of four Polyalthia species from Malaysia
    Shakri NM, Salleh WMNHW, Khamis S, Mohamad Ali NA, Shaharudin SM
    Z Naturforsch C J Biosci, 2020 Nov 26;75(11-12):473-478.
    PMID: 32628641 DOI: 10.1515/znc-2020-0097
    Polyalthia is one of the largest genera in the Annonaceae family, and has been widely used in folk medicine for the treatment of rheumatic fever, gastrointestinal ulcer, and generalized body pain. The present investigation reports on the extraction by hydrodistillation and the composition of the essential oils of four Polyalthia species (P. sumatrana, P. stenopetalla, P. cauliflora, and P. rumphii) growing in Malaysia. The chemical composition of these essential oils was determined by gas chromatography (GC-FID) and gas chromatography-mass spectrometry (GC-MS). The multivariate analysis was determined using principal component analysis (PCA) and hierarchical clustering analysis (HCA) methods. The results revealed that the studied essential oils are made up principally of bicyclogermacrene (18.8%), cis-calamenene (14.6%) and β-elemene (11.9%) for P. sumatrana; α-cadinol (13.0%) and δ-cadinene (10.2%) for P. stenopetalla; δ-elemene (38.1%) and β-cubebene (33.1%) for P. cauliflora; and finally germacrene D (33.3%) and bicyclogermacrene for P. rumphii. PCA score and HCA plots revealed that the essential oils were classified into three separated clusters of P. cauliflora (Cluster I), P. sumatrana (Cluster II), and P. stenopetalla, and P. rumphii (Cluster III) based on their characteristic chemical compositions. Our findings demonstrate that the essential oil could be useful for the characterization, pharmaceutical, and therapeutic applications of Polyalthia essential oil.
    Matched MeSH terms: Principal Component Analysis
  17. Signal Enhancement Evaluation of Laser-Induced Breakdown Spectroscopy of Extracted Animal Fats Using Principal Component Analysis Approach
    Hanasil NS, Raja Ibrahim RK, Duralim M, Sapingi HHJ, Mahdi MA
    Appl Spectrosc, 2020 Dec;74(12):1452-1462.
    PMID: 32166979 DOI: 10.1177/0003702820915532
    In this work, principal component analysis (PCA) was utilized to analyze laser-induced breakdown spectroscopy (LIBS) signals of the extracted chicken fat, lamb fat, beef fat, and lard froze using two different freezing methods. The frozen samples were ablated using a neodymium-doped yttrium aluminum garnet (Nd:YAG) laser with a wavelength of 1064 nm, 170 mJ pulse energy, and 6 ns pulse duration to produce plasma on target surfaces. The samples were ablated using 30-60 shots of the laser beam at different spots. Stronger LIBS signals from the extracted chicken fat and lamb fat were obtained with liquid nitrogen (LN2) method. However, LIBS signals obtained from the freezer freezing method were found to be stronger for extracted beef fat and lard. The PCA was then used to visualize the LIBS spectra of extracted animal fats into a score plot. Data points of each extracted animal fat were divided into three groups representing LIBS spectra collected at the early, middle, and end part of the ablation process. The score plot revealed that the data points of the three groups of frozen extracted animal fats using the LN2 method were more closely clustered than those frozen in the freezer. Good discrimination with 97% of the variance was achieved between the extracted chicken fat, lamb fat, beef fat, and lard using the LN2 method in the three-dimensional score plot. LIBS signals of the extracted animal fats produced from the LN2 method were found to be more stable than those from the freezer method.
    Matched MeSH terms: Principal Component Analysis
  18. Fulltext The PCA and LDA analysis on the differential expression of proteins in breast cancer
    Liang S, Singh M, Dharmaraj S, Gam LH
    Dis Markers, 2010;29(5):231-42.
    PMID: 21206008 DOI: 10.3233/DMA-2010-0753
    Breast cancer is a leading cause of mortality in women. In Malaysia, it is the most common cancer to affect women. The most common form of breast cancer is infiltrating ductal carcinoma (IDC). A proteomic approach was undertaken to identify protein profile changes between cancerous and normal breast tissues from 18 patients. Two protein extracts; aqueous soluble and membrane associated protein extracts were studied. Thirty four differentially expressed proteins were identified. The intensities of the proteins were used as variables in PCA and reduced data of six principal components (PC) were subjected to LDA in order to evaluate the potential of these proteins as collective biomarkers for breast cancer. The protein intensities of SEC13-like 1 (isoform b) and calreticulin contributed the most to the first PC while the protein intensities of fibrinogen beta chain precursor and ATP synthase D chain contributed the most to the second PC. Transthyretin precursor and apolipoprotein A-1 precursor contributed the most to the third PC. The results of LDA indicated good classification of samples into normal and cancerous types when the first 6 PCs were used as the variables. The percentage of correct classification was 91.7% for the originally grouped tissue samples and 88.9% for cross-validated samples.
    Matched MeSH terms: Principal Component Analysis
  19. Fulltext Genetic Variability, Heritability, and Clustering Pattern Exploration of Bambara Groundnut (Vigna subterranea L. Verdc) Accessions for the Perfection of Yield and Yield-Related Traits
    Khan MMH, Rafii MY, Ramlee SI, Jusoh M, Mamun A
    Biomed Res Int, 2020;2020:2195797.
    PMID: 33415143 DOI: 10.1155/2020/2195797
    Bambara groundnut (Vigna subterranea L. Verdc.) is considered an emerging crop for the future and known as a crop for the new millennium. The core intention of this research work was to estimate the variation of landraces of Bambara groundnut considering their 14 qualitative and 27 numerical traits, to discover the best genotype fitted in Malaysia. The findings of the ANOVA observed a highly significant variation (p ≤ 0.01) for all the traits evaluated. There was a substantial variation (7.27 to 41.21%) coefficient value, and 14 out of the 27 numerical traits noted coefficient of variation (CV) ≥ 20%. Yield (kg/ha) disclosed positively strong to perfect high significant correlation (r = 0.75 to 1.00; p ≤ 0.001) with traits like fresh pod weight, dry pod weight, and dry seed weight. The topmost PCV and GCV values were estimated for biomass dry (41.09%) and fresh (40.53%) weight with high heritability (Hb) and genetic advance (GA) Hb = 95.19%, GA = 80.57% and Hb = 98.52%, GA = 82.86%, respectively. The topmost heritability was recorded for fresh pod weight (99.89%) followed by yield (99.75%) with genetic advance 67.95% and 62.03%, respectively. The traits with Hb ≥ 60% and GA ≥ 20% suggested the least influenced by the environment as well as governed by the additive genes and direct selection for improvement of such traits can be beneficial. To estimate the genetic variability among accessions, the valuation of variance components, coefficients of variation, heritability, and genetic advance were calculated. To authenticate the genetic inequality, an unweighted pair group produced with arithmetic mean (UPGMA) and principal component analysis was executed based on their measurable traits that could be a steadfast method for judging the degree of diversity. Based on the UPGMA cluster analysis, constructed five distinct clusters and 44 accessions from clusters II and IV consider an elite type of genotypes that produce more than one ton yield per hectare land with desirable traits. This study exposed an extensive disparity among the landraces and the evidence on genetic relatives will be imperative in using the existing germplasm for Bambara groundnut varietal improvement. Moreover, this finding will be beneficial for breeders to choose the desirable numerical traits of V. subterranea in their future breeding program.
    Matched MeSH terms: Principal Component Analysis
  20. Phylogeography and ethnogenesis of aboriginal Southeast Asians
    Hill C, Soares P, Mormina M, Macaulay V, Meehan W, Blackburn J, et al.
    Mol Biol Evol, 2006 Dec;23(12):2480-91.
    PMID: 16982817
    Studying the genetic history of the Orang Asli of Peninsular Malaysia can provide crucial clues to the peopling of Southeast Asia as a whole. We have analyzed mitochondrial DNA (mtDNAs) control-region and coding-region markers in 447 mtDNAs from the region, including 260 Orang Asli, representative of each of the traditional groupings, the Semang, the Senoi, and the Aboriginal Malays, allowing us to test hypotheses about their origins. All of the Orang Asli groups have undergone high levels of genetic drift, but phylogeographic traces nevertheless remain of the ancestry of their maternal lineages. The Semang have a deep ancestry within the Malay Peninsula, dating to the initial settlement from Africa >50,000 years ago. The Senoi appear to be a composite group, with approximately half of the maternal lineages tracing back to the ancestors of the Semang and about half to Indochina. This is in agreement with the suggestion that they represent the descendants of early Austroasiatic speaking agriculturalists, who brought both their language and their technology to the southern part of the peninsula approximately 4,000 years ago and coalesced with the indigenous population. The Aboriginal Malays are more diverse, and although they show some connections with island Southeast Asia, as expected, they also harbor haplogroups that are either novel or rare elsewhere. Contrary to expectations, complete mtDNA genome sequences from one of these, R9b, suggest an ancestry in Indochina around the time of the Last Glacial Maximum, followed by an early-Holocene dispersal through the Malay Peninsula into island Southeast Asia.
    Matched MeSH terms: Principal Component Analysis
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