Displaying publications 81 - 100 of 167 in total

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  1. van der Ent A, Mak R, de Jonge MD, Harris HH
    Sci Rep, 2018 Jun 26;8(1):9683.
    PMID: 29946061 DOI: 10.1038/s41598-018-26891-7
    Hyperaccumulation is generally highly specific for a single element, for example nickel (Ni). The recently-discovered hyperaccumulator Glochidion cf. sericeum (Phyllanthaceae) from Malaysia is unusual in that it simultaneously accumulates nickel and cobalt (Co) with up to 1500 μg g-1 foliar of both elements. We set out to determine whether distribution and associated ligands for Ni and Co complexation differ in this species. We postulated that Co hyperaccumulation coincides with Ni hyperaccumulation operating on similar physiological pathways. However, the ostensibly lower tolerance for Co at the cellular level results in the exudation of Co on the leaf surface in the form of lesions. The formation of such lesions is akin to phytotoxicity responses described for manganese (Mn). Hence, in contrast to Ni, which is stored principally inside the foliar epidermal cells, the accumulation response to Co consists of an extracellular mechanism. The chemical speciation of Ni and Co, in terms of the coordinating ligands involved and principal oxidation state, is similar and associated with carboxylic acids (citrate for Ni and tartrate or malate for Co) and the hydrated metal ion. Some oxidation to Co3+, presumably on the surface of leaves after exudation, was observed.
    Matched MeSH terms: Least-Squares Analysis
  2. Yin YC, Ahmed J, Nee AYH, Hoe OK
    Environ Sci Pollut Res Int, 2023 Jan;30(3):5881-5902.
    PMID: 35982392 DOI: 10.1007/s11356-022-22271-x
    Sustainable and alternative energy sources of biofuel and solar power panel have been revolutionizing the lives and economy of many countries. However, these changes mainly occur in the urban areas and the rural population section has long been ignored by policy makers and government in the provision of energy. It is only recently that solar and biofuel are finally making in road to provide cheap and clean energy sources to rural population. As a result, literatures on consumer behavior of rural population towards sustainable energy sources are still very scarce. The present research aims to fulfill this gap by developing a conceptual model to investigate the adoption of solar power and biofuel energy resources in the cross-cultural setting of Malaysia and Pakistan. The data was collected from the rural areas of Pakistan and Malaysia. The two-stage data analysis method of partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) have been applied to satisfy both linear and non-linear regression assumptions, respectively. The results show that consumer in rural areas of Pakistan are willing and possess intention to adopt both biofuel and solar power for commercial and domestic use. Additionally, the results confirm that branding, economic, and altruistic factors are important in yielding intention to use towards biofuel and solar power panel in Pakistan which are validated by the results obtained in Malaysia. Other factors such as climate change awareness, retailer services quality, and ease of use are also important. The results offer wide-ranging theoretical and managerial implications.
    Matched MeSH terms: Least-Squares Analysis
  3. 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
  4. Ahirwal MK, Kumar A, Singh GK
    IEEE/ACM Trans Comput Biol Bioinform, 2013 Nov-Dec;10(6):1491-504.
    PMID: 24407307 DOI: 10.1109/TCBB.2013.119
    This paper explores the migration of adaptive filtering with swarm intelligence/evolutionary techniques employed in the field of electroencephalogram/event-related potential noise cancellation or extraction. A new approach is proposed in the form of controlled search space to stabilize the randomness of swarm intelligence techniques especially for the EEG signal. Swarm-based algorithms such as Particles Swarm Optimization, Artificial Bee Colony, and Cuckoo Optimization Algorithm with their variants are implemented to design optimized adaptive noise canceler. The proposed controlled search space technique is tested on each of the swarm intelligence techniques and is found to be more accurate and powerful. Adaptive noise canceler with traditional algorithms such as least-mean-square, normalized least-mean-square, and recursive least-mean-square algorithms are also implemented to compare the results. ERP signals such as simulated visual evoked potential, real visual evoked potential, and real sensorimotor evoked potential are used, due to their physiological importance in various EEG studies. Average computational time and shape measures of evolutionary techniques are observed 8.21E-01 sec and 1.73E-01, respectively. Though, traditional algorithms take negligible time consumption, but are unable to offer good shape preservation of ERP, noticed as average computational time and shape measure difference, 1.41E-02 sec and 2.60E+00, respectively.
    Matched MeSH terms: Least-Squares Analysis
  5. Rohman A, Man YC, Sismindari
    Pak J Pharm Sci, 2009 Oct;22(4):415-20.
    PMID: 19783522
    Today, virgin coconut oil (VCO) is becoming valuable oil and is receiving an attractive topic for researchers because of its several biological activities. In cosmetics industry, VCO is excellent material which functions as a skin moisturizer and softener. Therefore, it is important to develop a quantitative analytical method offering a fast and reliable technique. Fourier transform infrared (FTIR) spectroscopy with sample handling technique of attenuated total reflectance (ATR) can be successfully used to analyze VCO quantitatively in cream cosmetic preparations. A multivariate analysis using calibration of partial least square (PLS) model revealed the good relationship between actual value and FTIR-predicted value of VCO with coefficient of determination (R2) of 0.998.
    Matched MeSH terms: Least-Squares Analysis
  6. Sanagi MM, Ling SL, Nasir Z, Hermawan D, Ibrahim WA, Abu Naim A
    J AOAC Int, 2010 2 20;92(6):1833-8.
    PMID: 20166602
    LOD and LOQ are two important performance characteristics in method validation. This work compares three methods based on the International Conference on Harmonization and EURACHEM guidelines, namely, signal-to-noise, blank determination, and linear regression, to estimate the LOD and LOQ for volatile organic compounds (VOCs) by experimental methodology using GC. Five VOCs, toluene, ethylbenzene, isopropylbenzene, n-propylbenzene, and styrene, were chosen for the experimental study. The results indicated that the estimated LODs and LOQs were not equivalent and could vary by a factor of 5 to 6 for the different methods. It is, therefore, essential to have a clearly described procedure for estimating the LOD and LOQ during method validation to allow interlaboratory comparisons.
    Matched MeSH terms: Least-Squares Analysis
  7. Lim JH, Chinna K, Khosla P, Karupaiah T, Daud ZAM
    PMID: 33066603 DOI: 10.3390/ijerph17207479
    Dietary non-adherence is pervasive in the hemodialysis (HD) population. Health literacy is a plausible predictor of dietary adherence in HD patients, but its putative mechanism is scarcely studied. Thus, this study aimed to establish the causal model linking nutrition literacy to dietary adherence in the HD population. This was a multi-centre, cross-sectional study, involving 218 randomly selected multi-ethnic HD patients from nine dialysis centres in Klang Valley, Malaysia. Dietary adherence and self-management skills were assessed using validated End-Stage Renal Disease Adherence Questionnaire and Perceived Kidney/Dialysis Self-Management Scale, respectively. Validated self-developed scales were used to gauge nutrition literacy, dietary knowledge and Health Belief Model constructs. Relationships between variables were examined by multiple linear regressions and partial least squares structural equation modeling. Limited nutrition literacy was evident in 46.3% of the HD patients, associated with older age, lower education level, and shorter dialysis vintage. Dietary adherence rate was at 34.9%. Nutrition literacy (β= 0.390, p < 0.001) was an independent predictor of dietary adherence, mediated by self-efficacy (SIE = 0.186, BC 95% CI 0.110-0.280) and self-management skills (SIE = 0.192, BC 95% CI 0.103-0.304). Thus, nutrition literacy-enhancing strategies targeting self-efficacy and self-management skills should be considered to enhance dietary adherence in the HD population.
    Matched MeSH terms: Least-Squares Analysis
  8. Chau KY, Lam MHS, Cheung ML, Tso EKH, Flint SW, Broom DR, et al.
    Health Psychol Res, 2019 Mar 11;7(1):8099.
    PMID: 31583292 DOI: 10.4081/hpr.2019.8099
    Technological advancement and personalized health information has led to an increase in people using and responding to wearable technology in the last decade. These changes are often perceived to be beneficial, providing greater information and insights about health for users, organizations and healthcare and government. However, to date, understanding the antecedents of its adoption is limited. Seeking to address this gap, this cross-sectional study examined what factors influence users' adoption intention of healthcare wearable technology. We used self-administrated online survey to explore adoption intentions of healthcare wearable devices in 171 adults residing in Hong Kong. We analyzed the data by Partial least squares - structural equation modelling (PLS-SEM). The results reveal that perceived convenience and perceived irreplaceability are key predictors of perceived usefulness, which in turn strengthens users' adoption intention. Additionally, the results also reveal that health belief is one of the key predictors of adoption intention. This paper contributes to the extant literature by providing understanding of how to strengthen users' intention to adopt healthcare wearable technology. This includes the strengthening of perceived convenience and perceived irreplaceability to enhance the perceived usefulness, incorporating the extensive communication in the area of healthcare messages, which is useful in strengthening consumers' adoption intention in healthcare wearable technology.
    Matched MeSH terms: Least-Squares Analysis
  9. Ahmad SJ, Mohamad Zin N, Mazlan NW, Baharum SN, Baba MS, Lau YL
    PeerJ, 2021;9:e10816.
    PMID: 33777509 DOI: 10.7717/peerj.10816
    Background: Antiplasmodial drug discovery is significant especially from natural sources such as plant bacteria. This research aimed to determine antiplasmodial metabolites of Streptomyces spp. against Plasmodium falciparum 3D7 by using a metabolomics approach.

    Methods: Streptomyces strains' growth curves, namely SUK 12 and SUK 48, were measured and P. falciparum 3D7 IC50 values were calculated. Metabolomics analysis was conducted on both strains' mid-exponential and stationary phase extracts.

    Results: The most successful antiplasmodial activity of SUK 12 and SUK 48 extracts shown to be at the stationary phase with IC50 values of 0.8168 ng/mL and 0.1963 ng/mL, respectively. In contrast, the IC50 value of chloroquine diphosphate (CQ) for antiplasmodial activity was 0.2812 ng/mL. The univariate analysis revealed that 854 metabolites and 14, 44 and three metabolites showed significant differences in terms of strain, fermentation phase, and their interactions. Orthogonal partial least square-discriminant analysis and S-loading plot putatively identified pavettine, aurantioclavine, and 4-butyldiphenylmethane as significant outliers from the stationary phase of SUK 48. For potential isolation, metabolomics approach may be used as a preliminary approach to rapidly track and identify the presence of antimalarial metabolites before any isolation and purification can be done.

    Matched MeSH terms: Least-Squares Analysis
  10. Veerasamy R, Rajak H
    Turk J Pharm Sci, 2021 04 20;18(2):151-156.
    PMID: 33900700 DOI: 10.4274/tjps.galenos.2020.45556
    Objectives: The present study aimed to establish significant and validated quantitative structure-activity relationship (QSAR) models for neuraminidase inhibitors and correlate their physicochemical, steric, and electrostatic properties with their anti-influenza activity.

    Materials and Methods: We have developed and validated 2D and 3D QSAR models by using multiple linear regression, partial least square regression, and k-nearest neighbor-molecular field analysis methods.

    Results: 2D QSAR models had q2: 0.950 and pred_r2: 0.877 and 3D QSAR models had q2: 0.899 and pred_r2: 0.957. These results showed that the models werere predictive.

    Conclusion: Parameters such as hydrogen count and hydrophilicity were involved in 2D QSAR models. The 3D QSAR study revealed that steric and hydrophobic descriptors were negatively contributed to neuraminidase inhibitory activity. The results of this study could be used as platform for design of better anti-influenza drugs.

    Matched MeSH terms: Least-Squares Analysis
  11. Ahsan A, Wiyono NH, Veruswati M, Adani N, Kusuma D, Amalia N
    Global Health, 2020 07 18;16(1):65.
    PMID: 32682431 DOI: 10.1186/s12992-020-00595-y
    BACKGROUND: With a 264 million population and the second highest male smoking prevalence in the world, Indonesia hosted over 60 million smokers in 2018. However, the government still has not ratified the Framework Convention on Tobacco Control. In the meantime, tobacco import increases rapidly in Indonesia. These create a double, public health and economic burden for Indonesia's welfare.

    OBJECTIVE: Our study analyzed the trend of tobacco import in five countries: Indonesia, Pakistan, Bangladesh, Zimbabwe, and Mozambique. Also, we analyze the tobacco control policies implemented in these countries and determine some lessons learn for Indonesia.

    METHODS: We conducted quantitative analyses on tobacco production, consumption, export, and import during 1990-2016 in the five countries. Data were analyzed using simple ordinary least square regressions, correcting for time series autocorrelation. We also conducted a desk review on the tobacco control policies implemented in the five countries.

    RESULTS: While local production decreased by almost 20% during 1990-2016, the proportion of tobacco imports out of domestic production quadrupled from 17 to 65%. Similarly, the ratio of tobacco imports to exports reversed from 0.7 (i.e., exports were higher) to 2.9 (i.e., import were 2.9 times higher than export) in 1990 and 2016, respectively. This condition is quite different from the other four respective countries in the observation where their tobacco export is higher than the import. From the tobacco control point of view, the four other countries have ratified the Framework Convention on Tobacco Control (FCTC).

    CONCLUSION: The situation is unlikely for Indonesia to either reduce tobacco consumption or improve the local tobacco farmer's welfare, considering that the number of imports continued to increase. Emulating from the four countries, Indonesia must ratify the FCTC and implement stricter tobacco control policies to decrease tobacco consumption and import.

    Matched MeSH terms: Least-Squares Analysis
  12. Al-Okaily M, Alqudah H, Matar A, Lutfi A, Taamneh A
    Data Brief, 2020 Aug 18.
    PMID: 32837976 DOI: 10.1016/j.dib.2020.106176
    The COVID-19 pandemic has produced an unprecedented change in the educational system worldwide. Besides the economic and social impacts, there is a dilemma of accepting the new educational system "e-learning" by students within educational institutions. In particular, universities students have to handle several kinds of environmental, electronic and mental struggles due to COVID-19. To catch the current circumstances of more than two hundred thousand Jordanian university student during COVID-19. 2,500 students have been randomly selected to respond on an online survey using universities' portals and websites between March and April 2020. At the end of the data gathering process, we have received 587 records. The dataset includes 1) Demographics of students; 2) students' perspectives concerning the factors influencing their intention to use e-learning system within the Jordanian universities context. Data were analyzed using Partial Least Squares - Structural Equation Modelling (PLS-SEM). Next, the result has confirmed the positive of direct effect variables (subjective norm, perceived ease of use, and perceived usefulness) on the students' intention to use e-learning system. Next, the result has also confirmed the mediating effect of perceived usefulness and perceived ease of use between subjective norm and the behavioral intention to use the e-learning system with partially supported.
    Matched MeSH terms: Least-Squares Analysis
  13. Shahzad A, Hassan R, Aremu AY, Hussain A, Lodhi RN
    Qual Quant, 2020 Aug 04.
    PMID: 32836471 DOI: 10.1007/s11135-020-01028-z
    In response to the emerging and ever solution to the COVID-19 outbreak. This study proposes a theoretical framework based on literature and model to determined E-learning portal success. The study compared males and females to E-learning portal usage. The study objective is to check the difference between male and female E-learning portals' accessibility among the students' perspective. The study included service quality, system quality, information quality, user satisfaction, system use, and E-learning portal success. The empirical data of 280 students participated from the different universities of Malaysia through google surveys analyzed using the Partial Least Squares Structural Equation Modelling. The study further divided the full model into two domains, which are female and male. In the male model, information quality and system quality have direct relationships with user satisfaction. Information quality also supported the relationship with system use. At the same time, there is a positive relationship between user satisfaction and E-learning portals. Likewise, in the female model, E-service quality and Information quality both are supported by system use and user satisfaction. Similarly, system quality has a positive relationship with user satisfaction, and user satisfaction has a positive relationship with E-learning portals. The study will be further helpful for the Malaysian universities policy-makers such as top management, ministry of higher education, Malaysian universities union in designing the policies and programs on E-learning Portal Success in the country. The findings of the study reveal that males and females have a different level of in terms of usage of towards E-learning portals in Malaysian Universities.
    Matched MeSH terms: Least-Squares Analysis
  14. Lim V, Gorji SG, Daygon VD, Fitzgerald M
    Metabolites, 2020 Mar 19;10(3).
    PMID: 32204361 DOI: 10.3390/metabo10030114
    Selected Australian native fruits such as Davidson's plum, finger lime and native pepperberry have been reported to demonstrate potent antioxidant activity. However, comprehensive metabolite profiling of these fruits is limited, therefore the compounds responsible are unknown, and further, the compounds of nutritional value in these native fruits are yet to be described. In this study, untargeted and targeted metabolomics were conducted using the three fruits, together with assays to determine their antioxidant activities. The results demonstrate that targeted free and hydrolysed protein amino acids exhibited high amounts of essential amino acids. Similarly, important minerals like potassium were detected in the fruit samples. In antioxidant activity, Davidson's plum reported the highest activity in ferric reducing power (FRAP), finger lime in antioxidant capacity (ABTS), and native pepperberry in free radical scavenging (DPPH) and phosphomolybdenum assay. The compounds responsible for the antioxidant activity were tentatively identified using untargeted GC×GC-TOFMS and UHPLC-QqQ-TOF-MS/MS metabolomics. A clear discrimination into three clusters of fruits was observed using principal component analysis (PCA) and partial least squares (PLS) analysis. The correlation study identified a number of compounds that provide the antioxidant activities. GC×GC-TOFMS detected potent aroma compounds of limonene, furfural, and 1-R-α-pinene. Based on the untargeted and targeted metabolomics, and antioxidant assays, the nutritional potential of these Australian bush fruits is considerable and supports these indigenous fruits in the nutraceutical industry as well as functional ingredients for the food industry, with such outcomes benefiting Indigenous Australian communities.
    Matched MeSH terms: Least-Squares Analysis
  15. Saadatian-Elahi M, Alexander N, Möhlmann T, Langlois-Jacques C, Suer R, Ahmad NW, et al.
    Trials, 2021 May 30;22(1):374.
    PMID: 34053466 DOI: 10.1186/s13063-021-05298-2
    BACKGROUND: In common with many South East Asian countries, Malaysia is endemic for dengue. Dengue control in Malaysia is currently based on reactive vector management within 24 h of a dengue case being reported. Preventive rather than reactive vector control approaches, with combined interventions, are expected to improve the cost-effectiveness of dengue control programs. The principal objective of this cluster randomized controlled trial is to quantify the effectiveness of a preventive integrated vector management (IVM) strategy on the incidence of dengue as compared to routine vector control efforts.

    METHODS: The trial is conducted in randomly allocated clusters of low- and medium-cost housing located in the Federal Territory of Kuala Lumpur and Putrajaya. The IVM approach combines: targeted outdoor residual spraying with K-Othrine Polyzone, deployment of mosquito traps as auto-dissemination devices, and community engagement activities. The trial includes 300 clusters randomly allocated in a 1:1 ratio. The clusters receive either the preventive IVM in addition to the routine vector control activities or the routine vector control activities only. Epidemiological data from monthly confirmed dengue cases during the study period will be obtained from the Vector Borne Disease Sector, Malaysian Ministry of Health e-Dengue surveillance system. Entomological surveillance data will be collected in 12 clusters randomly selected from each arm. To measure the effectiveness of the IVM approach on dengue incidence, a negative binomial regression model will be used to compare the incidence between control and intervention clusters. To quantify the effect of the interventions on the main entomological outcome, ovitrap index, a modified ordinary least squares regression model using a robust standard error estimator will be used.

    DISCUSSION: Considering the ongoing expansion of dengue burden in Malaysia, setting up proactive control strategies is critical. Despite some limitations of the trial such as the use of passive surveillance to identify cases, the results will be informative for a better understanding of effectiveness of proactive IVM approach in the control of dengue. Evidence from this trial may help justify investment in preventive IVM approaches as preferred to reactive case management strategies.

    TRIAL REGISTRATION: ISRCTN ISRCTN81915073 . Retrospectively registered on 17 April 2020.

    Matched MeSH terms: Least-Squares Analysis
  16. Mat Dawi N, Namazi H, Maresova P
    Front Psychol, 2021;12:616749.
    PMID: 34093307 DOI: 10.3389/fpsyg.2021.616749
    Preventive behavior adoption is the key to reduce the possibility of getting COVID-19 infection. This paper aims to examine the determinants of intention to adopt preventive behavior by incorporating perception of e-government information and services and perception of social media into the theory of reasoned action. A cross-sectional online survey was carried out among Malaysian residents. Four hundred four valid responses were obtained and used for data analysis. A partial least-square-based path analysis revealed direct effects of attitude and subjective norm in predicting intention to adopt preventive behavior. In addition, perception of e-government information and services and perception of social media were found to be significant predictors of attitude toward preventive behavior. The findings highlight the importance of digital platforms in improving people's attitudes toward preventive behavior and in turn contain the spread of the infectious disease.
    Matched MeSH terms: Least-Squares Analysis
  17. 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
  18. 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
  19. Lee SY, Mediani A, Maulidiani M, Khatib A, Ismail IS, Zawawi N, et al.
    J Sci Food Agric, 2018 Jan;98(1):240-252.
    PMID: 28580581 DOI: 10.1002/jsfa.8462
    BACKGROUND: Neptunia oleracea is a plant consumed as a vegetable and which has been used as a folk remedy for several diseases. Herein, two regression models (partial least squares, PLS; and random forest, RF) in a metabolomics approach were compared and applied to the evaluation of the relationship between phenolics and bioactivities of N. oleracea. In addition, the effects of different extraction conditions on the phenolic constituents were assessed by pattern recognition analysis.

    RESULTS: Comparison of the PLS and RF showed that RF exhibited poorer generalization and hence poorer predictive performance. Both the regression coefficient of PLS and the variable importance of RF revealed that quercetin and kaempferol derivatives, caffeic acid and vitexin-2-O-rhamnoside were significant towards the tested bioactivities. Furthermore, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) results showed that sonication and absolute ethanol are the preferable extraction method and ethanol ratio, respectively, to produce N. oleracea extracts with high phenolic levels and therefore high DPPH scavenging and α-glucosidase inhibitory activities.

    CONCLUSION: Both PLS and RF are useful regression models in metabolomics studies. This work provides insight into the performance of different multivariate data analysis tools and the effects of different extraction conditions on the extraction of desired phenolics from plants. © 2017 Society of Chemical Industry.

    Matched MeSH terms: Least-Squares Analysis
  20. Maheshwari S, Pachori RB, Kanhangad V, Bhandary SV, Acharya UR
    Comput Biol Med, 2017 Sep 01;88:142-149.
    PMID: 28728059 DOI: 10.1016/j.compbiomed.2017.06.017
    Glaucoma is one of the leading causes of permanent vision loss. It is an ocular disorder caused by increased fluid pressure within the eye. The clinical methods available for the diagnosis of glaucoma require skilled supervision. They are manual, time consuming, and out of reach of common people. Hence, there is a need for an automated glaucoma diagnosis system for mass screening. In this paper, we present a novel method for an automated diagnosis of glaucoma using digital fundus images. Variational mode decomposition (VMD) method is used in an iterative manner for image decomposition. Various features namely, Kapoor entropy, Renyi entropy, Yager entropy, and fractal dimensions are extracted from VMD components. ReliefF algorithm is used to select the discriminatory features and these features are then fed to the least squares support vector machine (LS-SVM) for classification. Our proposed method achieved classification accuracies of 95.19% and 94.79% using three-fold and ten-fold cross-validation strategies, respectively. This system can aid the ophthalmologists in confirming their manual reading of classes (glaucoma or normal) using fundus images.
    Matched MeSH terms: Least-Squares Analysis
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