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Fulltext Development, validation and translation of cardiopulmonary resuscitation and automated external defibrillator training and placement bilingual questionnaire

Chew KS, Liaw SY, Ahmad Zahedi AZ, Wong SSL, Singmamae N, Kaushal DN, et al.

BMC Res Notes, 2019 Oct 21;12(1):670.
PMID: 31639035 DOI: 10.1186/s13104-019-4698-x

OBJECTIVES: This paper describes the development and translation of a questionnaire purported to measure (1) the perception of the placement strategy of automated external defibrillator, (2) the perception on the importance of bystander cardiopulmonary resuscitation and automated external defibrillator (3) the perception on the confidence and willingness to apply these two lifesaving interventions as well as (4) the fears and concerns in applying these two interventions. For construct validation, exploratory factor analysis was performed using principal axis factoring and promax oblique rotation and confirmatory factor analysis performed using partial least square.
RESULTS: Five factors with eigenvalue > 1 were identified. Pattern matrix analysis showed that all items were loaded into the factors with factor loading > 0.4. One item was subsequently removed as Cronbach's alpha > 0.9 which indicates redundancy. Confirmatory factor analysis demonstrated acceptable factor loadings except for one item which was subsequently removed. Internal consistency and discriminant validity was deemed acceptable with no significant cross-loading.

Matched MeSH terms: Least-Squares Analysis
Approximate bayesian estimates of weibull parameters with Lindley’s method

Chris Bambey Guure, Noor Akma Ibrahim

Sains Malaysiana, 2014;43:1433-1437.

One of the most important lifetime distributions that is used for modelling and analysing data in clinical, life sciences and engineering is the Weibull distribution. The main objective of this paper was to determine the best estimator for the two-parameter Weibull distribution. The methods under consideration are the frequentist maximum likelihood estimator, least square regression estimator and the Bayesian estimator by using two loss functions, which are squared error and linear exponential. Lindley approximation is used to obtain the Bayes estimates. Comparisons are made through simulation study to determine the performance of these methods. Based on the results obtained from this simulation study the Bayesian approach used in estimating the Weibull parameters under linear exponential loss function is found to be superior as compared to the conventional maximum likelihood and least squared methods.

Matched MeSH terms: Least-Squares Analysis
Evolutionary and ecological forces influencing population diversification in Bornean montane passerines

Chua VL, Smith BT, Burner RC, Rahman MA, Lakim M, Prawiradilaga DM, et al.

Mol Phylogenet Evol, 2017 Aug;113:139-149.
PMID: 28545973 DOI: 10.1016/j.ympev.2017.05.016

The mountains of Borneo are well known for their high endemicity and historical role in preserving Southeast Asian rainforest biodiversity, but the diversification of populations inhabiting these mountains is poorly studied. Here we examine the genetic structure of 12 Bornean montane passerines by comparing complete mtDNA ND2 gene sequences of populations spanning the island. Maximum likelihood and Bayesian phylogenetic trees and haplotype networks are examined for common patterns that might signal important historical events or boundaries to dispersal. Morphological and ecological characteristics of each species are also examined using phylogenetic generalized least-squares (PGLS) for correlation with population structure. Populations in only four of the 12 species are subdivided into distinct clades or haplotype groups. Although this subdivision occurred at about the same time in each species (ca. 0.6-0.7Ma), the spatial positioning of the genetic break differs among the species. In two species, northeastern populations are genetically divergent from populations elsewhere on the island. In the other two species, populations in the main Bornean mountain chain, including the northeast, are distinct from those on two isolated peaks in northwestern Borneo. We suggest different historical forces played a role in shaping these two distributions, despite commonality in timing. PGLS analysis showed that only a single characteristic-hand-wing index-is correlated with population structure. Birds with longer wings, and hence potentially more dispersal power, have less population structure. To understand historical forces influencing montane population structure on Borneo, future studies must compare populations across the entirety of Sundaland.

Matched MeSH terms: Least-Squares Analysis
A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant

Chun TS, Malek MA, Ismail AR

Water Sci Technol, 2015;71(4):524-8.
PMID: 25746643 DOI: 10.2166/wst.2014.451

The development of effluent removal prediction is crucial in providing a planning tool necessary for the future development and the construction of a septic sludge treatment plant (SSTP), especially in the developing countries. In order to investigate the expected functionality of the required standard, the prediction of the effluent quality, namely biological oxygen demand, chemical oxygen demand and total suspended solid of an SSTP was modelled using an artificial intelligence approach. In this paper, we adopt the clonal selection algorithm (CSA) to set up a prediction model, with a well-established method - namely the least-square support vector machine (LS-SVM) as a baseline model. The test results of the case study showed that the prediction of the CSA-based SSTP model worked well and provided model performance as satisfactory as the LS-SVM model. The CSA approach shows that fewer control and training parameters are required for model simulation as compared with the LS-SVM approach. The ability of a CSA approach in resolving limited data samples, non-linear sample function and multidimensional pattern recognition makes it a powerful tool in modelling the prediction of effluent removals in an SSTP.

Matched MeSH terms: Least-Squares Analysis
Fulltext Heat stress modifies the lactational performances and the urinary metabolomic profile related to gastrointestinal microbiota of dairy goats

Contreras-Jodar A, Nayan NH, Hamzaoui S, Caja G, Salama AAK

PLoS One, 2019;14(2):e0202457.
PMID: 30735497 DOI: 10.1371/journal.pone.0202457

The aim of the study is to identify the candidate biomarkers of heat stress (HS) in the urine of lactating dairy goats through the application of proton Nuclear Magnetic Resonance (1H NMR)-based metabolomic analysis. Dairy does (n = 16) in mid-lactation were submitted to thermal neutral (TN; indoors; 15 to 20°C; 40 to 45% humidity) or HS (climatic chamber; 37°C day, 30°C night; 40% humidity) conditions according to a crossover design (2 periods of 21 days). Thermophysiological traits and lactational performances were recorded and milk composition analyzed during each period. Urine samples were collected at day 15 of each period for 1H NMR spectroscopy analysis. Principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) assessment with cross validation were used to identify the goat urinary metabolome from the Human Metabolome Data Base. HS increased rectal temperature (1.2°C), respiratory rate (3.5-fold) and water intake (74%), but decreased feed intake (35%) and body weight (5%) of the lactating does. No differences were detected in milk yield, but HS decreased the milk contents of fat (9%), protein (16%) and lactose (5%). Metabolomics allowed separating TN and HS urinary clusters by PLS-DA. Most discriminating metabolites were hippurate and other phenylalanine (Phe) derivative compounds, which increased in HS vs. TN does. The greater excretion of these gut-derived toxic compounds indicated that HS induced a harmful gastrointestinal microbiota overgrowth, which should have sequestered aromatic amino acids for their metabolism and decreased the synthesis of neurotransmitters and thyroid hormones, with a negative impact on milk yield and composition. In conclusion, HS markedly changed the thermophysiological traits and lactational performances of dairy goats, which were translated into their urinary metabolomic profile through the presence of gut-derived toxic compounds. Hippurate and other Phe-derivative compounds are suggested as urinary biomarkers to detect heat-stressed dairy animals in practice.

Matched MeSH terms: Least-Squares Analysis
Fulltext Identifying Significant Metabolic Pathways Using Multi-Block Partial Least-Squares Analysis

Deng L, Guo F, Cheng KK, Zhu J, Gu H, Raftery D, et al.

J Proteome Res, 2020 05 01;19(5):1965-1974.
PMID: 32174118 DOI: 10.1021/acs.jproteome.9b00793

In metabolomics, identification of metabolic pathways altered by disease, genetics, or environmental perturbations is crucial to uncover the underlying biological mechanisms. A number of pathway analysis methods are currently available, which are generally based on equal-probability, topological-centrality, or model-separability methods. In brief, prior identification of significant metabolites is needed for the first two types of methods, while each pathway is modeled separately in the model-separability-based methods. In these methods, interactions between metabolic pathways are not taken into consideration. The current study aims to develop a novel metabolic pathway identification method based on multi-block partial least squares (MB-PLS) analysis by including all pathways into a global model to facilitate biological interpretation. The detected metabolites are first assigned to pathway blocks based on their roles in metabolism as defined by the KEGG pathway database. The metabolite intensity or concentration data matrix is then reconstructed as data blocks according to the metabolite subsets. Then, a MB-PLS model is built on these data blocks. A new metric, named the pathway importance in projection (PIP), is proposed for evaluation of the significance of each metabolic pathway for group separation. A simulated dataset was generated by imposing artificial perturbation on four pre-defined pathways of the healthy control group of a colorectal cancer study. Performance of the proposed method was evaluated and compared with seven other commonly used methods using both an actual metabolomics dataset and the simulated dataset. For the real metabolomics dataset, most of the significant pathways identified by the proposed method were found to be consistent with the published literature. For the simulated dataset, the significant pathways identified by the proposed method are highly consistent with the pre-defined pathways. The experimental results demonstrate that the proposed method is effective for identification of significant metabolic pathways, which may facilitate biological interpretation of metabolomics data.

Matched MeSH terms: Least-Squares Analysis
Sparse PLS-Based Method for Overlapping Metabolite Set Enrichment Analysis

Deng L, Ma L, Cheng KK, Xu X, Raftery D, Dong J

J Proteome Res, 2021 06 04;20(6):3204-3213.
PMID: 34002606 DOI: 10.1021/acs.jproteome.1c00064

Metabolite set enrichment analysis (MSEA) has gained increasing research interest for identification of perturbed metabolic pathways in metabolomics. The method incorporates predefined metabolic pathways information in the analysis where metabolite sets are typically assumed to be mutually exclusive to each other. However, metabolic pathways are known to contain common metabolites and intermediates. This situation, along with limitations in metabolite detection or coverage leads to overlapping, incomplete metabolite sets in pathway analysis. For overlapping metabolite sets, MSEA tends to result in high false positives due to improper weights allocated to the overlapping metabolites. Here, we proposed an extended partial least squares (PLS) model with a new sparse scheme for overlapping metabolite set enrichment analysis, named overlapping group PLS (ogPLS) analysis. The weight vector of the ogPLS model was decomposed into pathway-specific subvectors, and then a group lasso penalty was imposed on these subvectors to achieve a proper weight allocation for the overlapping metabolites. Two strategies were adopted in the proposed ogPLS model to identify the perturbed metabolic pathways. The first strategy involves debiasing regularization, which was used to reduce inequalities amongst the predefined metabolic pathways. The second strategy is stable selection, which was used to rank pathways while avoiding the nuisance problems of model parameter optimization. Both simulated and real-world metabolomic datasets were used to evaluate the proposed method and compare with two other MSEA methods including Global-test and the multiblock PLS (MB-PLS)-based pathway importance in projection (PIP) methods. Using a simulated dataset with known perturbed pathways, the average true discovery rate for the ogPLS method was found to be higher than the Global-test and the MB-PLS-based PIP methods. Analysis with a real-world metabolomics dataset also indicated that the developed method was less prone to select pathways with highly overlapped detected metabolite sets. Compared with the two other methods, the proposed method features higher accuracy, lower false-positive rate, and is more robust when applied to overlapping metabolite set analysis. The developed ogPLS method may serve as an alternative MSEA method to facilitate biological interpretation of metabolomics data for overlapping metabolite sets.

Matched MeSH terms: Least-Squares Analysis
Fulltext Rapid investigation of α-glucosidase inhibitory activity of Phaleria macrocarpa extracts using FTIR-ATR based fingerprinting

Easmin S, Sarker MZI, Ghafoor K, Ferdosh S, Jaffri J, Ali ME, et al.

J Food Drug Anal, 2017 Apr;25(2):306-315.
PMID: 28911672 DOI: 10.1016/j.jfda.2016.09.007

Phaleria macrocarpa, known as "Mahkota Dewa", is a widely used medicinal plant in Malaysia. This study focused on the characterization of α-glucosidase inhibitory activity of P. macrocarpa extracts using Fourier transform infrared spectroscopy (FTIR)-based metabolomics. P. macrocarpa and its extracts contain thousands of compounds having synergistic effect. Generally, their variability exists, and there are many active components in meager amounts. Thus, the conventional measurement methods of a single component for the quality control are time consuming, laborious, expensive, and unreliable. It is of great interest to develop a rapid prediction method for herbal quality control to investigate the α-glucosidase inhibitory activity of P. macrocarpa by multicomponent analyses. In this study, a rapid and simple analytical method was developed using FTIR spectroscopy-based fingerprinting. A total of 36 extracts of different ethanol concentrations were prepared and tested on inhibitory potential and fingerprinted using FTIR spectroscopy, coupled with chemometrics of orthogonal partial least square (OPLS) at the 4000-400 cm-1 frequency region and resolution of 4 cm-1. The OPLS model generated the highest regression coefficient with R2Y = 0.98 and Q2Y = 0.70, lowest root mean square error estimation = 17.17, and root mean square error of cross validation = 57.29. A five-component (1+4+0) predictive model was build up to correlate FTIR spectra with activity, and the responsible functional groups, such as -CH, -NH, -COOH, and -OH, were identified for the bioactivity. A successful multivariate model was constructed using FTIR-attenuated total reflection as a simple and rapid technique to predict the inhibitory activity.

Matched MeSH terms: Least-Squares Analysis
Liquid chromatography-tandem mass spectroscopic method for the determination of zerumbone in human plasma and its application to pharmacokinetics

Eid EE, Abdul AB, Rasedee A, Suliman FE, Sukari MA, Fatah SA

J Mass Spectrom, 2011 Aug;46(8):772-81.
PMID: 21834015 DOI: 10.1002/jms.1942

A rapid, sensitive, specific and selective LC-MS/MS method for the determination of zerumbone (ZER) in human plasma using 2,4-diamino-6-(4-methoxyphenyl)-1,3,5-triazine (DMTZ) as an internal standard (IS) has been developed and validated. ZER was chromatographed on C8 column using a mobile phase of acetonitrile/water (80:20, v/v) at a flow rate of 0.25 ml min(-1) . Quantitation was achieved using ESI+ interface, employing multiple reaction monitoring (MRM) mode at m/z 219 > 81 and 218 > 134 for ZER and IS, respectively. The calibration standards were linear over a range of 5-3000 ng ml(-1) (r(2)=0.9994) with an LLOQ of 5 ng ml(-1) (RSD %; 11.4% and bias%; 9.5%). Intra- and inter-day precision of ZER assay ranged from 0.18 to 3.56% with accuracy (bias) that varied between -5.09 and 4.3%, demonstrating good precision and accuracy. Recoveries of ZER and the IS from human plasma were above 85%. The developed method was validated for the determination of ZER in rat plasma. Linearity, stability of ZER and the ME on rat plasma were discussed. The applicability of the developed method was demonstrated by measuring ZER in rat plasma samples following intravenous and intraperitoneal administration of ZER prepared in hydroxypropyl-β-cyclodextrin (HPβCD) and sodium carboxymethyl cellulose (CMC), respectively, in 20 mg kg(-1) and this study indicated a clear significant difference (p<0.05) in pharmacokinetic parameters of ZER in ZER/HPβCD complex compared with ZER in CMC preparation.

Matched MeSH terms: Least-Squares Analysis
An eco-environmental efficiency analysis of Malaysia sewage treatment plants: an incorporated window-based data envelopment analysis and ordinary least square regression

Fallahiarezoudar E, Ahmadipourroudposht M, Yakideh K, Ngadiman NA

Environ Sci Pollut Res Int, 2022 May;29(25):38285-38302.
PMID: 35075563 DOI: 10.1007/s11356-022-18742-w

Most human activities that use water produced sewage. As urbanization grows, the overall demand for water grows. Correspondingly, the amount of produced sewage and pollution-induced water shortage is continuously increasing worldwide. Ensuring there are sufficient and safe water supplies for everyone is becoming increasingly challenging. Sewage treatment is an essential prerequisite for water reclamation and reuse. Sewage treatment plants' (STPs) performance in terms of economic and environmental perspective is known as a critical indicator for this purpose. Here, the window-based data envelopment analysis model was applied to dynamically assess the relative annual efficiency of STPs under different window widths. A total of five STPs across Malaysia were analyzed during 2015-2019. The labor cost, utility cost, operation cost, chemical consumption cost, and removal rate of pollution, as well as greenhouse gases' (GHGs) emissions, all were integrated to interpret the eco-environmental efficiency. Moreover, the ordinary least square as a supplementary method was used to regress the efficiency drivers. The results indicated the particular window width significantly affects the average of overall efficiencies; however, it shows no influence on the ranking of STP efficiency. The labor cost was determined as the most influential parameter, involving almost 40% of the total cost incurred. Hence, higher efficiency was observed with the larger-scale plants. Meanwhile, the statistical regression analysis illustrates the significance of plant scale, inflow cBOD concentrations, and inflow total phosphorus concentrations at [Formula: see text] on the performance. Lastly, some applicable techniques were suggested in terms of GHG emission mitigation.

Matched MeSH terms: Least-Squares Analysis
Behavioral pathways explaining oral health disparity in children

Gao XL, Hsu CY, Xu YC, Loh T, Koh D, Hwarng HB

J Dent Res, 2010 Sep;89(9):985-90.
PMID: 20554887 DOI: 10.1177/0022034510372896

Policymakers' understanding of and ability to reduce health disparities are pivotal for health promotion worldwide. This study aimed to verify the behavioral pathways leading to oral health disparities. Oral examinations were conducted for 1782 randomly selected preschoolers (3-6 yrs), and 1576 (88.4%) participants were followed up after 12 months. Parents were surveyed on their knowledge (K), attitude (A), and practices (P) regarding their children's oral health homecare (infant feeding, diet, and oral hygiene) and dental attendance. Structural equation modeling substantiated the links between specific KAs and corresponding practices, while generic KA did not affect practices. KAP pathways partly explained the ethnic and socio-economic disparities in oral health. Deprivation had a direct effect (not mediated by KA) on dental attendance, but not on oral health homecare. Ethnicity directly influenced oral health homecare practices, but not dental attendance. These behavioral pathways, furthering our understanding of health disparity, may have practical implications for health promotion and policy-making.

Matched MeSH terms: Least-Squares Analysis
QSAR and Pharmacophore Mapping Studies on Benzothiazinimines to Relate their Structural Features with anti-HIV Activity

Geethaavacini G, Poh GP, Yan LY, Deepashini R, Shalini S, Harish R, et al.

Med Chem, 2018;14(7):733-740.
PMID: 29807521 DOI: 10.2174/1573406414666180529091618

BACKGROUND: The development of severe drug resistance caused by the extensive use of anti-HIV agents has resulted in a greatly extensive reduction in these drugs efficacy.
OBJECTIVES: To identify the important pharmacophoric features and correlate 3D chemical structure of benzothiazinimines with their anti-HIV potential using 2D, 3D-QSAR and pharmacophore modeling studies.
METHODS: QSAR and pharmacophore mapping studies have been used to relate structural features. 2D QSAR and 3D QSAR studies were performed using partial least square and k-nearest neighbor methodology, coupled with various feature selection methods, viz. stepwise, genetic algorithm, and simulated annealing, to derive QSAR models which were further validated for statistical significance.
RESULTS: The physicochemical descriptor XAHydrophilicArea and SsOHE-index, and alignmentindependent descriptor T_C_Cl_6 showed significant correlation with the anti-HIV activity of benzothiazinimines in 2D QSAR. 3D QSAR results showed the significant effect of electrostatic and steric field descriptors in the anti-HIV potential of benzothiazinimines. The generated pharmacophore hypothesis demonstrated the importance of aromaticity and hydrogen bond acceptors.
CONCLUSION: The significant models obtained in this study suggested that these techniques could be used as a guidance for designing new benzothiazinimines with enhanced anti-HIV potential.

Matched MeSH terms: Least-Squares Analysis
A transport environmental Kuznets curve analysis for Malaysia: exploring the role of corruption

Go YH, Lau LS, Liew FM, Senadjki A

Environ Sci Pollut Res Int, 2021 Jan;28(3):3421-3433.
PMID: 32918263 DOI: 10.1007/s11356-020-10736-w

Validity of the environmental Kuznets curve (EKC) hypothesis is consistently and widely debated among economists and environmentalists alike throughout time. In Malaysia, transport is one of the "dirtiest" sectors; it intensively consumes energy in powering engines by using fossil fuels and poses significant threats to environmental quality. Therefore, this study attempted an examination into the impact of corruption on transport carbon dioxide (CO2) emissions. By adopting the fully modified ordinary least squares, canonical cointegrating regression, and dynamic ordinary least squares in performing long-run estimations, the results obtained based on the annual data spanning from 1990 to 2017 yielded various notable findings. First, more corruption would be attributable towards increased transport CO2 emissions. Second, a monotonic increment of transport CO2 emission was seen with higher economic growth and thus invalidated the presence of EKC. Overall, this study suggests that Malaysia has yet to reach the level of economic growth synonymous with transport CO2 emission reduction due to the lack of high technology usage in the current system implemented. Therefore, this study could position policy recommendations of use to the Malaysian authorities in designing the appropriate economic and environmental policies, particularly for the transport sector.

Matched MeSH terms: Least-Squares Analysis
Rapid assessment of total MCPD esters in palm-based cooking oil using ATR-FTIR application and chemometric analysis

Goh KM, Maulidiani M, Rudiyanto R, Wong YH, Ang MY, Yew WM, et al.

Talanta, 2019 Jun 01;198:215-223.
PMID: 30876552 DOI: 10.1016/j.talanta.2019.01.111

The technique of Fourier transform infrared spectroscopy is widely used to generate spectral data for use in the detection of food contaminants. Monochloropropanediol (MCPD) is a refining process-induced contaminant that is found in palm-based fats and oils. In this study, a chemometric approach was used to evaluate the relationship between the FTIR spectra and the total MCPD content of a palm-based cooking oil. A total of 156 samples were used to develop partial least squares regression (PLSR), artificial neural network (nnet), average artificial neural network (avNNET), random forest (RF) and cubist models. In addition, a consensus approach was used to generate fusion result consisted from all the model mentioned above. All the models were evaluated based on validation performed using training and testing datasets. In addition, the box plot of coefficient of determination (R2), root mean square error (RMSE), slopes and intercepts by 100 times randomization was also compared. Evaluation of performance based on the testing R2 and RMSE suggested that the cubist model predicted total MCPD content with the highest accuracy, followed by the RF, avNNET, nnet and PLSR models. The overfitting tendency was assessed based on differences in R2 and RMSE in the training and testing calibrations. The observations showed that the cubist and avNNET models possessed a certain degree of overfitting. However, the accuracy of these models in predicting the total MCPD content was high. Results of the consensus model showed that it slightly improved the accuracy of prediction as well as significantly reduced its uncertainty. The important variables derived from the cubist and RF models suggested that the wavenumbers corresponding to the MCPDs originated from the -CH=CH2 or CH=CH (990-900 cm-1) and C-Cl stretch (800-700 cm-1) regions of the FTIR spectrum data. In short, chemometrics in combination with FTIR analysis especially for the consensus model represent a potential and flexible technique for estimating the total MCPD content of refined vegetable oils.

Matched MeSH terms: Least-Squares Analysis
Fulltext Salivary bacterial shifts in oral leukoplakia resemble the dysbiotic oral cancer bacteriome

Gopinath D, Kunnath Menon R, Chun Wie C, Banerjee M, Panda S, Mandal D, et al.

J Oral Microbiol, 2020 Dec 09;13(1):1857998.
PMID: 33391629 DOI: 10.1080/20002297.2020.1857998

Objective: While some oral carcinomas appear to arise de novo, others develop within long-standing conditions of the oral cavity that have malignant potential, now known as oral potentially malignant disorders (OPMDs). The oral bacteriome associated with OPMD has been studied to a lesser extent than that associated with oral cancer. To characterize the association in detail we compared the bacteriome in whole mouth fluid (WMF) in patients with oral leukoplakia, oral cancer and healthy controls. Methods: WMF bacteriome from 20 leukoplakia patients, 31 patients with oral cancer and 23 healthy controls were profiled using the Illumina MiSeq platform. Sequencing reads were processed using DADA2, and taxonomical classification was performed using the phylogenetic placement method. Sparse Partial Least Squares Regression Discriminant Analysis model was used to identify bacterial taxa that best discriminate the studied groups. Results: We found considerable overlap between the WMF bacteriome of leukoplakia and oral cancer while a clearer separation between healthy controls and the former two disorders was observed. Specifically, the separation was attributed to 14 taxa belonging to the genera Megaspheara, unclassified enterobacteria, Prevotella, Porphyromonas, Rothia and Salmonella, Streptococcus, and Fusobacterium. The most discriminative bacterial genera between leukoplakia and oral cancer were Megasphaera, unclassified Enterobacteriae, Salmonella and Prevotella.Conclusion: Oral bacteria may play a role in the early stages of oral carcinogenesis as a dysbiotic bacteriome is associated with oral leukoplakia and this resembles that of oral cancer more than healthy controls. Our findings may have implications for developing oral cancer prevention strategies targeting early microbial drivers of oral carcinogenesis.

Matched MeSH terms: Least-Squares Analysis
Measurement and dimension of road fatality in Brunei

Haque MO

Int J Inj Contr Saf Promot, 2011 Mar;18(1):45-55.
PMID: 21409677 DOI: 10.1080/17457300.2010.517319

In this article, we have investigated the pattern of road fatality in Brunei. It is seen from this analysis that road fatality in Brunei was one of the highest in the world in the early 1990s, but has been significantly reduced over the years, and is now one of the lowest in the world. Preliminary investigation shows that young male drivers are responsible for most road fatalities in Brunei. We have also fitted a linear regression model and found that road fatality is significantly positively related to people aged 18-24 years and new registered vehicles, both of which are expected to grow with the growth of population and economic development. Hence, road fatality in Brunei is also expected to grow unless additional effective road safety countermeasures are introduced and implemented to reduce road toll. Negative coefficient is observed for trend variable, indicating the reduction of road fatality due to the combined effects of improvements of vehicle safety, road design, medical facilities and road safety awareness among road user groups. However, short-term road fatality analysis based on monthly data indicates that the coefficient of the trend variable is positive, implying that in recent months road fatalities are increasing in Brunei, which is supported by media reports. We have compared Brunei's road fatality data with Australia, Singapore and Malaysia and found that Brunei's road fatality rate is lower than Singapore and Malaysia, but higher than Australia. This indicates that there are still opportunities to reduce road fatalities in Brunei if additional effective road safety strategies are implemented like in Australia without interfering in the economic and social development of Brunei.

Matched MeSH terms: Least-Squares Analysis
A new hybrid intelligent system for accurate detection of Parkinson's disease

Hariharan M, Polat K, Sindhu R

Comput Methods Programs Biomed, 2014 Mar;113(3):904-13.
PMID: 24485390 DOI: 10.1016/j.cmpb.2014.01.004

Elderly people are commonly affected by Parkinson's disease (PD) which is one of the most common neurodegenerative disorders due to the loss of dopamine-producing brain cells. People with PD's (PWP) may have difficulty in walking, talking or completing other simple tasks. Variety of medications is available to treat PD. Recently, researchers have found that voice signals recorded from the PWP is becoming a useful tool to differentiate them from healthy controls. Several dysphonia features, feature reduction/selection techniques and classification algorithms were proposed by researchers in the literature to detect PD. In this paper, hybrid intelligent system is proposed which includes feature pre-processing using Model-based clustering (Gaussian mixture model), feature reduction/selection using principal component analysis (PCA), linear discriminant analysis (LDA), sequential forward selection (SFS) and sequential backward selection (SBS), and classification using three supervised classifiers such as least-square support vector machine (LS-SVM), probabilistic neural network (PNN) and general regression neural network (GRNN). PD dataset was used from University of California-Irvine (UCI) machine learning database. The strength of the proposed method has been evaluated through several performance measures. The experimental results show that the combination of feature pre-processing, feature reduction/selection methods and classification gives a maximum classification accuracy of 100% for the Parkinson's dataset.

Matched MeSH terms: Least-Squares Analysis
Evaluation of Chilling Injury in Mangoes Using Multispectral Imaging

Hashim N, Onwude DI, Osman MS

J Food Sci, 2018 May;83(5):1271-1279.
PMID: 29660789 DOI: 10.1111/1750-3841.14127

Commodities originating from tropical and subtropical climes are prone to chilling injury (CI). This injury could affect the quality and marketing potential of mango after harvest. This will later affect the quality of the produce and subsequent consumer acceptance. In this study, the appearance of CI symptoms in mango was evaluated non-destructively using multispectral imaging. The fruit were stored at 4 °C to induce CI and 12 °C to preserve the quality of the control samples for 4 days before they were taken out and stored at ambient temperature for 24 hr. Measurements using multispectral imaging and standard reference methods were conducted before and after storage. The performance of multispectral imaging was compared using standard reference properties including moisture content (MC), total soluble solids (TSS) content, firmness, pH, and color. Least square support vector machine (LS-SVM) combined with principal component analysis (PCA) were used to discriminate CI samples with those of control and before storage, respectively. The statistical results demonstrated significant changes in the reference quality properties of samples before and after storage. The results also revealed that multispectral parameters have a strong correlation with the reference parameters of L* , a* , TSS, and MC. The MC and L* were found to be the best reference parameters in identifying the severity of CI in mangoes. PCA and LS-SVM analysis indicated that the fruit were successfully classified into their categories, that is, before storage, control, and CI. This indicated that the multispectral imaging technique is feasible for detecting CI in mangoes during postharvest storage and processing.
PRACTICAL APPLICATION: This paper demonstrates a fast, easy, and accurate method of identifying the effect of cold storage on mango, nondestructively. The method presented in this paper can be used industrially to efficiently differentiate different fruits from each other after low temperature storage.

Matched MeSH terms: Least-Squares Analysis
Fulltext NMR-Based Metabolomics Profiling for Radical Scavenging and Anti-Aging Properties of Selected Herbs

Hussin M, Abdul Hamid A, Abas F, Ramli NS, Jaafar AH, Roowi S, et al.

Molecules, 2019 Sep 03;24(17).
PMID: 31484470 DOI: 10.3390/molecules24173208

Herbs that are usually recognized as medicinal plants are well known for their therapeutic effects and are traditionally used to treat numerous diseases, including aging. This study aimed to evaluate the metabolite variations among six selected herbs namely Curcurmalonga, Oenanthejavanica, Vitex negundo, Plucheaindica, Cosmoscaudatus and Persicariaminus using proton nuclear magnetic resonance (1H-NMR) coupled with multivariate data analysis (MVDA). The free radical scavenging activity of the extract was measured by 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2-azinobis(3-ethyl-benzothiazoline-6-sulfonic acid) (ABTS) and oxygen radical absorbance capacity (ORAC) assay. The anti-aging property was characterized by anti-elastase and anti-collagenase inhibitory activities. The results revealed that P. minus showed the highest radical scavenging activities and anti-aging properties. The partial least squares (PLS) biplot indicated the presence of potent metabolites in P. minus such as quercetin, quercetin-3-O-rhamnoside (quercitrin), myricetin derivatives, catechin, isorhamnetin, astragalin and apigenin. It can be concluded that P. minus can be considered as a potential source for an anti-aging ingredient and also a good free radical eradicator. Therefore, P. minus could be used in future development in anti-aging researches and medicinal ingredient preparations.

Matched MeSH terms: Least-Squares Analysis
Regression methods to investigate the relationship between facial measurements and widths of the maxillary anterior teeth

Isa ZM, Tawfiq OF, Noor NM, Shamsudheen MI, Rijal OM

J Prosthet Dent, 2010 Mar;103(3):182-8.
PMID: 20188241 DOI: 10.1016/S0022-3913(10)60028-5

In rehabilitating edentulous patients, selecting appropriately sized teeth in the absence of preextraction records is problematic.

Matched MeSH terms: Least-Squares Analysis

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