Genetic structure and biodiversity of the medicinal plant Ficus deltoidea have rarely been scrutinized. To fill these lacunae, five varieties, consisting of 30 F. deltoidea accessions were collected across the country and studied on the basis of molecular and morphological data. Molecular analysis of the accessions was performed using nine Inter Simple Sequence Repeat (ISSR) markers, seven of which were detected as polymorphic markers. ISSR-based clustering generated four clusters supporting the geographical distribution of the accessions to some extent. The Jaccard's similarity coefficient implied the existence of low diversity (0.50-0.75) in the studied population. STRUCTURE analysis showed a low differentiation among the sampling sites, while a moderate varietal differentiation was unveiled with two main populations of F. deltoidea. Our observations confirmed the occurrence of gene flow among the accessions; however, the highest degree of this genetic interference was related to the three accessions of FDDJ10, FDTT16 and FDKT25. These three accessions may be the genetic intervarietal fusion points of the plant's population. Principal Components Analysis (PCA) relying on quantitative morphological characteristics resulted in two principal components with Eigenvalue >1 which made up 89.96% of the total variation. The cluster analysis performed by the eight quantitative characteristics led to grouping the accessions into four clusters with a Euclidean distance ranged between 0.06 and 1.10. Similarly, a four-cluster dendrogram was generated using qualitative traits. The qualitative characteristics were found to be more discriminating in the cluster and PCA analyses, while ISSRs were more informative on the evolution and genetic structure of the population.
Data from three published studies of genetic variation at 18 microsatellite loci in water buffalo populations in China (18 swamp type, two river type), Nepal (one wild, one domestic river, one hybrid) and south-east Asia (eight swamp, three river) were combined so as to gain a broader understanding of genetic relationships among the populations and their demographic history. Mean numbers of alleles and expected heterozygosities were significantly different among populations. Estimates of θ (a measure of population differentiation) were significant among the swamp populations for all loci and among the river populations for most loci. Differentiation among the Chinese swamp populations (which was due primarily to just one population) was much less than among the south-east Asian. The Nepal wild animals, phenotypically swamp type but genetically like river type, are significantly different from all the domestic river populations and presumably represent the ancestral Bubalus arnee (possibly with some river-type introgression). Relationships among the swamp populations (D(A) genetic distances, principal component analysis and structure analyses) show the south-east Asian populations separated into two groups by the Chinese populations. Given these relationships and the patterns of genetic variability, we postulate that the swamp buffalo was domesticated in the region of the far south of China, northern Thailand and Indochina. Following domestication, it spread south through peninsular Malaysia to Sumatra, Java and Sulawesi, and north through China, and then to Taiwan, the Philippines and Borneo.
In a reconnaisance soil geochemical and plant survey undertaken to study the heavy metal uptake by major food crops in Malaysia, 241 soils were analysed for cation exchange capacity (CEC), organic carbon (C), pH, electrical conductivity (EC) and available phosphorus (P) using appropriate procedures. These soils were also analysed for arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb) and zinc (Zn) using aqua regia digestion, together with 180 plant samples using nitric acid digestion. Regression analysis between the edible plant part and aqua regia soluble soil As, Cd, Cr, Cu, Hg, Ni, Pb and Zn concentrations sampled throughout Peninsular Malaysia, indicated a positive relationship for Pb in all the plants sampled in the survey (R2 = 0.195, p < 0.001), for Ni in corn (R2 = 0.649, p < 0.005), for Cu in chili (R2 = 0.344, p < 0.010) and for Zn in chili (R2 = 0.501, p < 0.001). Principal component analysis of the soil data suggested that concentrations of Co, Ni, Pb and Zn were strongly correlated with concentrations of Al and Fe, which is suggestive of evidence of background variations due to changes in soil mineralogy. Thus the evidence for widespread contamination of soils by these elements through agricultural activities is not strong. Chromium was correlated with soil pH and EC, Na, S, and Ca while Hg was not correlated with any of these components, suggesting diffuse pollution by aerial deposition. However As, Cd, Cu were strongly associated with organic matter and available and aqua regia soluble soil P, which we attribute to inputs in agricultural fertilisers and soil organic amendments (e.g. manures, composts).
This study analyzed the volatile organic compounds (VOCs) of three mango varieties (Harumanis, Tong Dam and Susu) for the discrimination of authentic Harumanis from other mangoes. The VOCs of these mangoes were extracted and analysed nondestructively using Head Space-Solid Phase Micro Extraction (HS-SPME) coupled to Gas Chromatography-Mass Spectrometry (GC-MS). Prior to the analytical method, two simple sensory analyses were carried out to assess the ability of the consumers to differentiate between the Harumanis and Tong Dam mangoes as well as their preferences towards these mangoes. On the other hand, chemometrics techniques, such as principal components analysis (PCA), hierarchical clustering analysis (HCA), and discriminant analysis (DA), were used to visualise grouping tendencies of the volatile compounds detected. These techniques were successful in identifying the grouping tendencies of the mango samples according to the presence of their respective volatile compounds, thus enabling the identification of the groups of substances responsible for the discrimination between the authentic and unauthentic Harumanis mangoes. In addition, three ocimene compounds, namely beta-ocimene, trans beta-ocimene, and allo-ocimene, can be considered as chemical markers of the Harumanis mango, as these compounds exist in all Harumanis mango, regardless the different sources of the mangoes obtained.
An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together.
Matched MeSH terms: Principal Component Analysis/methods
Weedy rice (WR) is found in many direct-seeded rice fields. WR possesses morphological characteristics that are similar to cultivated rice varieties in the early stage of growth, making them more difficult to control than other weeds. A comparative morphological study was conducted by collecting WR accessions from four sites within the Pulau Pinang rice growing areas. The objective of the study was to characterise WR accessions of the Pulau Pinang rice granary by comparing their morphological characteristics to those of commercially grown rice in the area. Their morphometric relations were established by comparing 17 morphological characteristics of the WR accessions and the commercial varieties. A total of 36 WR morphotypes were identified from these 4 sites based on 17 characteristics, which included grain shattering habit and germination rate. The Principal Component Analysis (PCA) showed that 45.88% of the variation observed among the WR accessions and commercial varieties were within the first 3 axes. PB6, PP2 and SGA5 WR accessions had a higher number of tillers and longer panicle lengths, culm heights and leaf lengths compared to the commercial rice. The grain
sizes of the commercial varieties were slightly longer, and the chlorophyll contents at 60–70 days after sowing (DAS) were higher than those of the WR accessions. Results from this study are useful for predicting potential WR accession growth, which might improve WR management and agriculture practices that control WR in the future.
BACKGROUND: Body image dissatisfaction among breast cancer survivors has been associated with psychological stress resultant from breast cancer and resultant surgery. This study aimed to examine the psychometric properties of the Malay Version of the Breast-Impact of Treatment Scale (MVBITS) and to investigate the associations of retained factors with the Hospital Anxiety and Depression Scale (HADS) and the Rosenberg Self-Esteem Scale (RSES).
MATERIALS AND METHODS: The MVBITS was 'forward-backward' translated from English to Malay and then administered to 70 female breast cancer patients who came to the Oncology Clinic of University Malaya Medical Centre, Kuala Lumpur, Malaysia to undergo chemotherapy. Principal component analysis (PCA) with varimax rotation was performed to explore the factor structure of the MVBITS. Associations of retained factors were estimated with reference to Spearman correlation coefficients.
RESULTS: The internal consistency reliability of MVBITS was good (Cronbach's alpha 0.945) and showed temporal stability over a 3-week period. Principal component analysis suggested two factors termed as 'Intrusion' and 'Avoidance' domains. These factors explained 70.3% of the variance. Factor 1 comprised the effects of breast cancer treatment on the emotion and thought, while Factor 2 informed attempts to limit exposure of the body to self or others. The Factor 1 of MVBITS was positively correlated with total, depression and anxiety sub-scores of HADS. Factor 2 was positively correlated with total and anxiety sub-scores of HADS. MVBITS was also positively correlated with the RSES scores.
CONCLUSIONS: The results showed that the Malay Version of Breast-Impact of Treatment Scale possesses satisfactory psychometric properties suggesting that this instrument is appropriate for assessment of body change stress among female breast cancer patients in Malaysia.
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.
Harumanis is one of the main signatures of Perlis with regards to its delightful taste, pleasant aroma and expensive price. Harumanis authenticity and productivity had become the remarks among the farmers, entrepreneurs, consumers and plant breeders due to the existence of morphological characteristics variation among the fruits and high production cost. Assessment of Harumanis morphological characteristics of natural population and different tree ages may represent a possible source of important characteristics for development and breeding purposes of Harumanis. The aim of this study is to evaluate the morphological variation of Harumanis collected from different location in Perlis and tree age. A total of 150 Harumanis fruits from 50 trees with three different stages of development (young, middle-aged and old) were characterised using 11 traits; 10 quantitative and one qualitative morphological trait. The ANOVA analyses in combination with Dunn's pairwise and Kruskal-Wallis multiple comparison test able to point out the existence of environmental factor and age influence towards the significant different of identified morphological traits except for Total Soluble Solid (TSS) and pulp percentage. Five clusters of 50 Harumanis accessions reflect a grouping pattern which not according to neither geographical region nor age. The result of Principal Component Analysis (PCA) using the first two principal components (PCs) provided a good approximation of the data explaining 84.09% of the total variance which majorly contributed by parameters of weight, fruit dimensional characteristics, peel percentage and hue angle, h. Preliminary screening of important morphological characteristics which contribute to the phenotypic diversity of Harumanis is successfully achieved. The findings can be employed by the plant breeders and farmers for the establishment of standard grading of Harumanis and advancement of breeding crop of Harumanis in future.
Ground reaction force (GRF) is a key metric in biomechanical research, including parameters of loading rate (LR), first impact peak, second impact peak, and transient between first and second impact peaks in heel strike runners. The GRFs vary over time during stance. This study was aimed to investigate the variances of GRFs in rearfoot striking runners across incremental speeds. Thirty female and male runners joined the running tests on the instrumented treadmill with speeds of 2.7, 3.0, 3.3, and 3.7 m/s. The discrete parameters of vertical average loading rate in the current study are consistent with the literature findings. The principal component analysis was modeled to investigate the main variances (95%) in the GRFs over stance. The females varied in the magnitude of braking and propulsive forces (PC1, 84.93%), whereas the male runners varied in the timing of propulsion (PC1, 53.38%). The female runners dominantly varied in the transient between the first and second peaks of vertical GRF (PC1, 36.52%) and LR (PC2, 33.76%), whereas the males variated in the LR and second peak of vertical GRF (PC1, 78.69%). Knowledge reported in the current study suggested the difference of the magnitude and patterns of GRF between male and female runners across different speeds. These findings may have implications for the prevention of sex-specific running-related injuries and could be integrated with wearable signals for the in-field prediction and estimation of impact loadings and GRFs.
BACKGROUND/OBJECTIVES: Little is known about the dietary patterns (DPs) of women during pregnancy. The present study aimed to identify the DPs of pregnant Malaysian women and their associations with socio-demographic, obstetric, and anthropometric characteristics.
SUBJECTS AND METHODS: This prospective cohort study included 737 participants enrolled in Seremban Cohort Study between 2013 and 2015. Food consumption was assessed using a validated 126-food item semi-quantitative food frequency questionnaire (SFFQ) at four time-points, namely, pre-pregnancy and at each trimester (first, second, and third). Principal component analysis (PCA) was used to identify DPs.
RESULTS: Three DPs were identified at each time point and designated DP 1-3 (pre-pregnancy), DP 4-6 (first trimester), DP 7-9 (second trimester) and DP 10-12 (third trimester). DP 1, 4, and 7 appeared to be more prudent diets, characterized by higher intakes of nuts, seeds & legumes, green leafy vegetables, other vegetables, eggs, fruits, and milk & dairy products. DP 2, 5, 8, and 11 had greater loadings of condiments & spices, sugar, spreads & creamer, though DP 2 had additional sweet foods, DP 5 and 8 had additional oils & fats, and DP 11 had additional tea & coffee, respectively. DP 3 and 6 were characterized by high protein (poultry, meat, processed, dairy, eggs, and fish), sugars (mainly as beverages and sweet foods), and energy (bread, cereal & cereal products, rice, noodles & pasta) intakes. DP 9 had additional fruits. However, DP 12 had greater loadings of energy foods (bread, cereal & cereal products, rice, noodles & pasta), sugars (mainly as beverages, and sweet foods), and good protein sources (eggs, nuts, seeds & legumes). Malays were more likely to have lower adherence (LA) for DP 1 and 10 than non-Malays. DP 2, 8, and 11 were more prevalent among Malays than non-Malays. Women with a higher education were more likely to have LA for DP 10, and women with a greater waist circumference at first prenatal visit were more likely to show LA for DP 11.
CONCLUSIONS: DPs observed in the present study were substantially different from those reported in Western populations. Information concerning associations between ethnicity, waist circumference and education with specific DPs before and throughout pregnancy could facilitate efforts to promote healthy dietary behavior and the overall health and well-being of pregnant women.
Study name: Seremban Cohort Study (SECOST)
BACKGROUND AND OBJECTIVE: For diagnosis of arrhythmic heart problems, electrocardiogram (ECG) signals should be recorded and monitored. The long-term signal records obtained are analyzed by expert cardiologists. Devices such as the Holter monitor have limited hardware capabilities. For improved diagnostic capacity, it would be helpful to detect arrhythmic signals automatically. In this study, a novel approach is presented as a candidate solution for these issues.
METHODS: A convolutional auto-encoder (CAE) based nonlinear compression structure is implemented to reduce the signal size of arrhythmic beats. Long-short term memory (LSTM) classifiers are employed to automatically recognize arrhythmias using ECG features, which are deeply coded with the CAE network.
RESULTS: Based upon the coded ECG signals, both storage requirement and classification time were considerably reduced. In experimental studies conducted with the MIT-BIH arrhythmia database, ECG signals were compressed by an average 0.70% percentage root mean square difference (PRD) rate, and an accuracy of over 99.0% was observed.
CONCLUSIONS: One of the significant contributions of this study is that the proposed approach can significantly reduce time duration when using LSTM networks for data analysis. Thus, a novel and effective approach was proposed for both ECG signal compression, and their high-performance automatic recognition, with very low computational cost.
Introduction: Globally, the prevalence of cardiovascular diseases (CVD) is high in Punjabi population. This could due to the increased cardiometabolic risks associated with diets high in dietary fats and refined grains. However, studies on the relationship between dietary pattern and cardiometabolic risks involving Malaysian Punjabis popu- lation are scarce. Hence, this study aims to determine the associations between dietary patterns and cardiometa- bolic risks in Malaysian Punjabi adults. Methods: Socio-demographic, lifestyle and dietary intake information was collected using self-administered questionnaire. Anthropometric measurements: weight and height for body mass index (BMI) calculation, waist circumference (WC); systolic (SBP) and diastolic blood pressure (DBP); and biomark- ers: blood glucose, glycated haemoglobin A1c (HbA1c), triglycerides, total cholesterol (TC), low-density-lipopro- tein cholesterol (LDL-C), high-density-lipoprotein cholesterol (HDL-C), apolipoprotein A1 and B100 were obtained. Major dietary patterns were derived using principal component analysis. Association between dietary patterns and cardiometabolic risk factors were performed using ANCOVA and Kruskal-Wallis tests. Results: A total of 164 (35.4% males and 64.6% females) Punjabis were included in this study. Four dietary patterns were extracted, namely ‘fruits and vegetables diet’ (FVD), ‘whole grains, condiments and beverages diet’ (WCBD), ‘protein diet’ (PD) and ‘rice, noodles, cereals and meat diet’ (RNCMD). Significant associations were obtained for FVD with BMI (p=0.012), WC (p=0.011), SBP (p=0.020) and DBP (p=0.009); WCBD with TC (p=0.010), LDL-C (p=0.015) and apolipoprotein B100 (p=0.038). Conclusion: Dietary pattern comprised of fruits, vegetables and beverages containing antioxidant-rich spices, ginger, and black tea may lower cardiometabolic risks in Malaysian Punjabis, particularly in obesity, high blood pressure and hyperlipidaemia.
Ancestry-informative markers (AIMs) can be used to infer the ancestry of an individual to minimize the inaccuracy of self-reported ethnicity in biomedical research. In this study, we describe three methods for selecting AIM SNPs for the Malay population (Malay AIM panel) using different approaches based on pairwise FST, informativeness for assignment (In), and PCA-correlated SNPs (PCAIMs). These Malay AIM panels were extracted from genotype data stored in SNP arrays hosted by the Malaysian node of the Human Variome Project (MyHVP) and the Singapore Genome Variation Project (SGVP). In particular, genotype data from a total of 165 Malay individuals were analyzed, comprising data on 117 individual genotypes from the Affymetrix SNP-6 SNP array platform and data on 48 individual genotypes from the OMNI 2.5 Illumina SNP array platform. The HapMap phase 3 database (1397 individuals from 11 populations) was used as a reference for comparison with the Malay genotype data. The accuracy of each resulting Malay AIM panel was evaluated using a machine learning "ancestry-predictive model" constructed by using WEKA, a comprehensive machine learning platform written in Java. A total of 1250 SNPs were finally selected, which successfully identified Malay individuals from other world populations with an accuracy of 90%, but the accuracy decreased to 80% using 157 SNPs according to the pairwise FST method, while a panel of 200 SNPs selected using In and PCAIMs could be used to identify Malay individuals with an accuracy of approximately 80%.
Malay, the main ethnic group in Peninsular Malaysia, is represented by various sub-ethnic groups such as Melayu Banjar, Melayu Bugis, Melayu Champa, Melayu Java, Melayu Kedah Melayu Kelantan, Melayu Minang and Melayu Patani. Using data retrieved from the MyHVP (Malaysian Human Variome Project) database, a total of 135 individuals from these sub-ethnic groups were profiled using the Affymetrix GeneChip Mapping Xba 50-K single nucleotide polymorphism (SNP) array to identify SNPs that were ancestry-informative markers (AIMs) for Malays of Peninsular Malaysia. Prior to selecting the AIMs, the genetic structure of Malays was explored with reference to 11 other populations obtained from the Pan-Asian SNP Consortium database using principal component analysis (PCA) and ADMIXTURE. Iterative pruning principal component analysis (ipPCA) was further used to identify sub-groups of Malays. Subsequently, we constructed an AIMs panel for Malays using the informativeness for assignment (In) of genetic markers, and the K-nearest neighbor classifier (KNN) was used to teach the classification models. A model of 250 SNPs ranked by In, correctly classified Malay individuals with an accuracy of up to 90%. The identified panel of SNPs could be utilized as a panel of AIMs to ascertain the specific ancestry of Malays, which may be useful in disease association studies, biomedical research or forensic investigation purposes.
To investigate the breeding habitat preference of black flies, a comprehensive black fly survey was conducted for the first time in Peninsular Malaysia. Preimaginal black flies (pupae and larvae) were collected manually from 180 stream points encompassing northern, southern, central and east coast of the Peninsular Malaysia. A total of 47 black fly species were recorded in this study. The predominant species were Simulium trangense (36.7%) and Simulium angulistylum (33.3%). Relatively common species were Simulium cheongi (29.4%), Simulium tani (25.6%), Simulium nobile (16.2%), Simulium sheilae (14.5%) and Simulium bishopi (10.6%). Principal Component Analysis (PCA) of all stream variables revealed four PCs that accounted for 69.3% of the total intersite variance. Regression analysis revealed that high species richness is associated with larger, deeper, faster and higher discharge streams with larger streambed particles, more riparian vegetation and low pH (F=22.7, d.f.=1, 173; P<0.001). Relationship between species occurrence of seven common species (present in >10% of the sampling sites) was assessed. Forward logistic regression analysis indicated that four species were significantly related to the stream variables. S. nobile and S. tani prefer large, fast flowing streams with higher pH, large streambed particles and riparian trees. S. bishopi was commonly found at high elevation with cooler stream, low conductivity, higher conductivity and more riparian trees. In contrast, S. sheilae was negatively correlated with PC-2, thus, this species commonly found at low elevation, warmer stream with low conductivity and less riparian trees. The results of this study are consistent with previous studies from other geographic regions, which indicated that both physical and chemical stream conditions are the key factors for black fly ecology.
The biofilm-forming-capability of Helicobacter pylori has been suggested to be among factors influencing treatment outcome. However, H. pylori exhibit strain-to-strain differences in biofilm-forming-capability. Metabolomics enables the inference of spatial and temporal changes of metabolic activities during biofilm formation. Our study seeks to examine the differences in metabolome of low and high biofilm-formers using the metabolomic approach. Eight H. pylori clinical strains with different biofilm-forming-capability were chosen for metabolomic analysis. Bacterial metabolites were extracted using Bligh and Dyer method and analyzed by Liquid Chromatography/Quadrupole Time-of-Flight mass spectrometry. The data was processed and analyzed using the MassHunter Qualitative Analysis and the Mass Profiler Professional programs. Based on global metabolomic profiles, low and high biofilm-formers presented as two distinctly different groups. Interestingly, low-biofilm-formers produced more metabolites than high-biofilm-formers. Further analysis was performed to identify metabolites that differed significantly (p-value
Zoo animal welfare is a high priority for many institutions worldwide, with modern zoos now ensuring that animals are housed and cared for to the highest standards. However, in countries where this knowledge is not as available or understood, standards may be lower. The aim of this research was to investigate if there were common zoo welfare concerns across developing country zoos. Wild Welfare is a charity working globally to improve welfare for zoo animals and has an independent welfare audit that is carried out before any intervention occurs. The Wild Welfare Audit, consisting of 110 questions, covering nine topics, was completed at 11 zoos in seven developing countries (Brazil, Egypt, Libya, Indonesia, Thailand, Malaysia and Vietnam) following a Likert scale score (1-3). A principal component analysis was also performed to evaluate the audit questions. The results suggest that common areas of concern were animal behaviour, positive animal mental states and human health and safety. These themes were likely due to the lack knowledge and understanding that may be linked to historical and cultural differences. This research has helped to revise the welfare audit as well as inform future intervention strategies for improving developing country zoo animal welfare.
Multivariate stable isotope analysis combined with chemometrics was used to investigate and discriminate rice samples from six rice producing provinces in China (Heilongjiang, Jilin, Jiangsu, Zhejiang, Hunan and Guizhou) and four other Asian rice producing countries (Thailand, Malaysia, Philippines, and Pakistan). The stable isotope characteristics were analyzed for rice of different species cultivated with varied farming methods at different altitudes and latitudes/longitudes. The index groups of δ13C, δ15N, δ18O, 207/206Pb and 208/207Pb were screened and established for the selected samples with different geographical features by means of principal component analysis (PCA) and discriminant analysis (DA), which would provide a sound technical solution for rice traceability and serve as a template for further research on the traceability of other agricultural products, especially plant-derived products.