Displaying publications 81 - 100 of 311 in total

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  1. Influence of initial dissolved oxygen concentration on Fenton's reagent degradation
    Aris A, Sharratt PN
    Environ Technol, 2006 Oct;27(10):1153-61.
    PMID: 17144264
    The effect of initial dissolved oxygen concentration (IDOC) on Fenton's reagent degradation of a dyestuff, Reactive Black 5 was explored in this study. The study was designed, conducted and analysed based on Central Composite Rotatable Design using a 3-1 lab-scale reactor. The participation of O2 in the process was experimentally observed and appears to be affected by the dosage of the reagents used in the study. The IDOC was found to have a significant influence on the process. Reducing the IDOC from 7.5 mg l(-1) to 2.5 mg l(-1) increased the removal of TOC by an average of about 10%. Reduction of IDOC from 10 mg l(-1) to 0 mg l(-1) enhanced the TOC removal by about 30%. The negative influence of IDOC is likely to be caused by the competition between the O2 and the reagents for the organoradicals. A model describing the relationship between initial TOC removal, reagent dosage and IDOC has also been developed.
    Matched MeSH terms: Models, Statistical
  2. Optimization of nitrogen and phosphorus limitation for better biodegradable plastic production and organic removal using single fed-batch mixed cultures and renewable resources
    Din MF, Ujang Z, van Loosdrecht MC, Ahmad A, Sairan MF
    Water Sci Technol, 2006;53(6):15-20.
    PMID: 16749434
    The process for the production of biodegradable plastic material (polyhydroxyalkanoates, PHAs) from microbial cells by mixed-bacterial cultivation using readily available waste (renewable resources) is the main consideration nowadays. These observations have shown impressive results typically under high carbon fraction, COD/N and COD/P (usually described as nutrient-limiting conditions) and warmest temperature (moderate condition). Therefore, the aim of this work is predominantly to select mixed cultures under high storage responded by cultivation on a substrate - non limited in a single batch reactor with shortest period for feeding and to characterize their storage response by using specific and kinetics determination. In that case, the selected-fixed temperature is 30 degrees C to establish tropical conditions. During the accumulated steady-state period, the cell growth was inhibited by high PHA content within the cells because of the carbon reserve consumption. From the experiments, there is no doubt about the PHA accumulation even at high carbon fraction ratio. Apparently, the best accumulation occurred at carbon fraction, 160 +/- 7.97 g COD/g N (PHAmean, = 44.54% of dried cells). Unfortunately, the highest PHA productivity was achieved at the high carbon fraction, 560 +/- 1.62 g COD/g N (0.152 +/- 0.17 g/l. min). Overall results showed that with high carbon fraction induced to the cultivation, the PO4 and NO3 can remove up to 20% in single cultivation.
    Matched MeSH terms: Models, Statistical
  3. Fulltext Bayesian inference of the Weibull model based on interval-censored survival data
    Guure CB, Ibrahim NA, Adam MB
    Comput Math Methods Med, 2013;2013:849520.
    PMID: 23476718 DOI: 10.1155/2013/849520
    Interval-censored data consist of adjacent inspection times that surround an unknown failure time. We have in this paper reviewed the classical approach which is maximum likelihood in estimating the Weibull parameters with interval-censored data. We have also considered the Bayesian approach in estimating the Weibull parameters with interval-censored data under three loss functions. This study became necessary because of the limited discussion in the literature, if at all, with regard to estimating the Weibull parameters with interval-censored data using Bayesian. A simulation study is carried out to compare the performances of the methods. A real data application is also illustrated. It has been observed from the study that the Bayesian estimator is preferred to the classical maximum likelihood estimator for both the scale and shape parameters.
    Matched MeSH terms: Models, Statistical
  4. Impact of the effect of economic crisis and the targeted motorcycle safety programme on motorcycle-related accidents, injuries and fatalities in Malaysia
    Law TH, Umar RS, Zulkaurnain S, Kulanthayan S
    Int J Inj Contr Saf Promot, 2005 Mar;12(1):9-21.
    PMID: 15814371
    In 1997, a Motorcycle Safety Programme (MSP) was introduced to address the motorcycle-related accident problem. The MSP was specifically targeted at motorcyclists. In addition to the MSP, the recent economic recession has significantly contributed to a reduction of traffic-related incidents. This paper examines the effects of the recent economic crisis and the MSP on motorcycle-related accidents, casualties and fatalities in Malaysia. The autocorrelation integrated moving average model with transfer function was used to evaluate the overall effects of the interventions. The variables used in developing the model were gross domestic product and MSPs. The analysis found a 25% reduction in the number of motorcycle-related accidents, a 27% reduction in motorcycle casualties and a 38% reduction in motorcycle fatalities after the implementation of MSP. Findings indicate that the MSP has been one of the effective measures in reducing motorcycle safety problems in Malaysia. Apart from that, the performance of the country's economy was also found to be significant in explaining the number of motorcycle-related accidents, casualties and fatalities in Malaysia.
    Matched MeSH terms: Models, Statistical
  5. Fulltext An Efficient Optimization Method for Solving Unsupervised Data Classification Problems
    Shabanzadeh P, Yusof R
    Comput Math Methods Med, 2015;2015:802754.
    PMID: 26336509 DOI: 10.1155/2015/802754
    Unsupervised data classification (or clustering) analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications. In general, there is no single algorithm that is suitable for all types of data, conditions, and applications. Each algorithm has its own advantages, limitations, and deficiencies. Hence, research for novel and effective approaches for unsupervised data classification is still active. In this paper a heuristic algorithm, Biogeography-Based Optimization (BBO) algorithm, was adapted for data clustering problems by modifying the main operators of BBO algorithm, which is inspired from the natural biogeography distribution of different species. Similar to other population-based algorithms, BBO algorithm starts with an initial population of candidate solutions to an optimization problem and an objective function that is calculated for them. To evaluate the performance of the proposed algorithm assessment was carried on six medical and real life datasets and was compared with eight well known and recent unsupervised data classification algorithms. Numerical results demonstrate that the proposed evolutionary optimization algorithm is efficient for unsupervised data classification.
    Matched MeSH terms: Models, Statistical
  6. Fulltext Application of an Effective Statistical Technique for an Accurate and Powerful Mining of Quantitative Trait Loci for Rice Aroma Trait
    Golestan Hashemi FS, Rafii MY, Ismail MR, Mohamed MT, Rahim HA, Latif MA, et al.
    PLoS One, 2015;10(6):e0129069.
    PMID: 26061689 DOI: 10.1371/journal.pone.0129069
    When a phenotype of interest is associated with an external/internal covariate, covariate inclusion in quantitative trait loci (QTL) analyses can diminish residual variation and subsequently enhance the ability of QTL detection. In the in vitro synthesis of 2-acetyl-1-pyrroline (2AP), the main fragrance compound in rice, the thermal processing during the Maillard-type reaction between proline and carbohydrate reduction produces a roasted, popcorn-like aroma. Hence, for the first time, we included the proline amino acid, an important precursor of 2AP, as a covariate in our QTL mapping analyses to precisely explore the genetic factors affecting natural variation for rice scent. Consequently, two QTLs were traced on chromosomes 4 and 8. They explained from 20% to 49% of the total aroma phenotypic variance. Additionally, by saturating the interval harboring the major QTL using gene-based primers, a putative allele of fgr (major genetic determinant of fragrance) was mapped in the QTL on the 8th chromosome in the interval RM223-SCU015RM (1.63 cM). These loci supported previous studies of different accessions. Such QTLs can be widely used by breeders in crop improvement programs and for further fine mapping. Moreover, no previous studies and findings were found on simultaneous assessment of the relationship among 2AP, proline and fragrance QTLs. Therefore, our findings can help further our understanding of the metabolomic and genetic basis of 2AP biosynthesis in aromatic rice.
    Matched MeSH terms: Models, Statistical
  7. Fulltext Fractional Diffusion Based Modelling and Prediction of Human Brain Response to External Stimuli
    Namazi H, Kulish VV
    Comput Math Methods Med, 2015;2015:148534.
    PMID: 26089955 DOI: 10.1155/2015/148534
    Human brain response is the result of the overall ability of the brain in analyzing different internal and external stimuli and thus making the proper decisions. During the last decades scientists have discovered more about this phenomenon and proposed some models based on computational, biological, or neuropsychological methods. Despite some advances in studies related to this area of the brain research, there were fewer efforts which have been done on the mathematical modeling of the human brain response to external stimuli. This research is devoted to the modeling and prediction of the human EEG signal, as an alert state of overall human brain activity monitoring, upon receiving external stimuli, based on fractional diffusion equations. The results of this modeling show very good agreement with the real human EEG signal and thus this model can be used for many types of applications such as prediction of seizure onset in patient with epilepsy.
    Matched MeSH terms: Models, Statistical
  8. Fulltext A Unified Framework for Brain Segmentation in MR Images
    Yazdani S, Yusof R, Karimian A, Riazi AH, Bennamoun M
    Comput Math Methods Med, 2015;2015:829893.
    PMID: 26089978 DOI: 10.1155/2015/829893
    Brain MRI segmentation is an important issue for discovering the brain structure and diagnosis of subtle anatomical changes in different brain diseases. However, due to several artifacts brain tissue segmentation remains a challenging task. The aim of this paper is to improve the automatic segmentation of brain into gray matter, white matter, and cerebrospinal fluid in magnetic resonance images (MRI). We proposed an automatic hybrid image segmentation method that integrates the modified statistical expectation-maximization (EM) method and the spatial information combined with support vector machine (SVM). The combined method has more accurate results than what can be achieved with its individual techniques that is demonstrated through experiments on both real data and simulated images. Experiments are carried out on both synthetic and real MRI. The results of proposed technique are evaluated against manual segmentation results and other methods based on real T1-weighted scans from Internet Brain Segmentation Repository (IBSR) and simulated images from BrainWeb. The Kappa index is calculated to assess the performance of the proposed framework relative to the ground truth and expert segmentations. The results demonstrate that the proposed combined method has satisfactory results on both simulated MRI and real brain datasets.
    Matched MeSH terms: Models, Statistical
  9. Regional assessment of LV wall in infarcted heart using tagged MRI and cardiac modelling
    Jahanzad Z, Liew YM, Bilgen M, McLaughlin RA, Leong CO, Chee KH, et al.
    Phys Med Biol, 2015 May 21;60(10):4015-31.
    PMID: 25919317 DOI: 10.1088/0031-9155/60/10/4015
    A segmental two-parameter empirical deformable model is proposed for evaluating regional motion abnormality of the left ventricle. Short-axis tagged MRI scans were acquired from 10 healthy subjects and 10 postinfarct patients. Two motion parameters, contraction and rotation, were quantified for each cardiac segment by fitting the proposed model using a non-rigid registration algorithm. The accuracy in motion estimation was compared to a global model approach. Motion parameters extracted from patients were correlated to infarct transmurality assessed with delayed-contrast-enhanced MRI. The proposed segmental model allows markedly improved accuracy in regional motion analysis as compared to the global model for both subject groups (1.22-1.40 mm versus 2.31-2.55 mm error). By end-systole, all healthy segments experienced radial displacement by ~25-35% of the epicardial radius, whereas the 3 short-axis planes rotated differently (basal: 3.3°; mid:  -1° and apical:  -4.6°) to create a twisting motion. While systolic contraction showed clear correspondence to infarct transmurality, rotation was nonspecific to either infarct location or transmurality but could indicate the presence of functional abnormality. Regional contraction and rotation derived using this model could potentially aid in the assessment of severity of regional dysfunction of infarcted myocardium.
    Matched MeSH terms: Models, Statistical
  10. "Power quality system," a new system of quality management for globalization: towards innovation and competitive advantages
    Abdul-Rahman H, Berawi MA
    Qual Assur, 2001;9(1):5-30.
    PMID: 12465710
    Knowledge Management (KM) addresses the critical issues of organizational adoption, survival and competence in the face of an increasingly changing environment. KM embodies organizational processes that seek a synergistic combination of the data and information processing capabilities of information and communication technologies (ICT), and the creative and innovative capacity of human beings to improve ICT In that role, knowledge management will improve quality management and avoid or minimize losses and weakness that usually come from poor performance as well as increase the competitive level of the company and its ability to survive in the global marketplace. To achieve quality, all parties including the clients, company consultants, contractors, entrepreneurs, suppliers, and the governing bodies (i.e., all involved stake-holders) need to collaborate and commit to achieving quality. The design based organizations in major business and construction companies have to be quality driven to support healthy growth in today's competitive market. In the march towards vision 2020 and globalization (i.e., the one world community) of many companies, their design based organizations need to have superior quality management and knowledge management to anticipate changes. The implementation of a quality system such as the ISO 9000 Standards, Total Quality Management, or Quality Function Deployment (QFD) focuses the company's resources towards achieving faster and better results in the global market with less cost. To anticipate the needs of the marketplace and clients as the world and technology change, a new system, which we call Power Quality System (PQS), has been designed. PQS is a combination of information and communication technologies (ICT) and the creative and innovative capacity of human beings to meet the challenges of the new world business and to develop high quality products.
    Publication year= 2001 Jan-2002 Mar
    Matched MeSH terms: Models, Statistical
  11. A proposed hierarchical fuzzy inference system for the diagnosis of arthritic diseases
    Lim CK, Yew KM, Ng KH, Abdullah BJ
    Australas Phys Eng Sci Med, 2002 Sep;25(3):144-50.
    PMID: 12416592 DOI: 10.1007/BF03178776
    Development of computer-based medical inference systems is always confronted with some difficulties. In this paper, difficulties of designing an inference system for the diagnosis of arthritic diseases are described, including variations of disease manifestations under various situations and conditions. Furthermore, the need for a huge knowledge base would result in low efficiency of the inference system. We proposed a hierarchical model of the fuzzy inference system as a possible solution. With such a model, the diagnostic process is divided into two levels. The first level of the diagnosis reduces the scope of diagnosis to be processed by the second level. This will reduce the amount of input and mapping for the whole diagnostic process. Fuzzy relational theory is the core of this system and it is used in both levels to improve the accuracy.
    Matched MeSH terms: Models, Statistical
  12. Immunization coverage required to prevent outbreaks of dog rabies
    Coleman PG, Dye C
    Vaccine, 1996 Feb;14(3):185-6.
    PMID: 8920697
    WHO recommends that 70% of dogs in a population should be immunized to eliminate or prevent outbreaks of rabies. This critical percentage (pc) has been established empirically from observations on the relationship between vaccination coverage and rabies incidence in dog populations around the world. Here, by contrast, we estimate pc by using epidemic theory, together with data available from four outbreaks in urban and rural areas of the USA, Mexico, Malaysia and Indonesia. From the rate of increase of cases at the beginning of these epidemics, we obtain estimates of the basic case reproduction number of infection, R0, in the range 1.62-2.33, implying that pc lies between 39% and 57%. The errors attached to these estimates of pc suggest that the recommended coverage of 70% would prevent a major outbreak of rabies on no fewer than 96.5% of occasions.
    Matched MeSH terms: Models, Statistical
  13. Regional inequalities of child mortality in peninsular Malaysia with special reference to the differentials between Perlis and Kuala Terengganu
    Brehm U
    Soc Sci Med, 1993 May;36(10):1331-4.
    PMID: 8511619
    In Peninsular Malaysia child mortality rates (5q0) vary from 13 to 63 per thousand at district level. The spatial pattern is closely associated with the regional distribution of socio-economic factors. But due to multicollinearity it is difficult to isolate the influence of socio-economic variables from other variables by employing aggregated data. However, individual data collected in a case-control-study that was conducted in Perlis and Kuala Terengganu confirm the important role of socio-economic factors. So it should be possible to achieve a further reduction of child mortality by raising the income and educational level of the under-privileged groups. Apart from that, as the case of Perlis shows, the provision of family planning and preventive medical services may also contribute to lower child mortality independent from socio-economic changes. But, as the comparison with Kuala Terengganu shows, the utilization of family planning and preventive medical services is not only influenced by the accessibility to, but also by the socio-culturally determined acceptability of such services.
    Matched MeSH terms: Models, Statistical
  14. Fulltext Intravenous immunoglobulin in the therapeutic armamentarium of systemic lupus erythematosus: a systematic review and meta-analysis
    Sakthiswary R, D'Cruz D
    Medicine (Baltimore), 2014 Oct;93(16):e86.
    PMID: 25310743 DOI: 10.1097/MD.0000000000000086
    Prepared from the plasma of thousands of blood donors, therapeutic intravenous immunoglobulin (IVIg) mostly consists of human polyspecific immunoglobulin G (IgG). The use of IVIg in systemic lupus erythematosus (SLE) is still considered experimental without any clear indications. The purpose of this systematic review is, therefore, to evaluate the available evidence to determine the therapeutic role of IVIg in SLE. A comprehensive, computerised search was performed in the MEDLINE (Pubmed), Scopus, EMBASE, and Cochrane controlled trials. The study eligibility criteria were randomized controlled trials, and prospective and retrospective observational studies that examined the efficacy of IVIg in adult patients with SLE who were considered the participants.IVIg therapy was the mode of intervention in these patients. Data abstracted included the study design, study population, changes in the disease activity scores (Systemic Lupus Erythematosus Disease Activity Index, Systemic Lupus Activity Measure, and Lupus Activity Index-Pregnancy), steroid dose, complement levels, autoantibodies, and renal function. Thereafter, data analysis established statistical procedures for meta-analysis. Thirteen studies (including 3 controlled and 10 observational) were eligible for inclusion. There was significant reduction in the SLE disease activity scores with IVIg therapy with a standard mean difference of 0.584 (P = 0.002, 95% confidence interval [CI] 0.221-0.947). In terms of rise in complement levels, the response rate was 30.9% (P = 0.001, 95 CI 22.1-41.3). The effects of IVIg on other clinical outcome measures including anti-double-stranded DNA, antinuclear antibody, average steroid dose, and renal function could not be determined because of the limited numbers of trials. The limitations of this review were lack of well-designed controlled trials with adequate sample size on the use of IVIg in SLE. In conclusion, the use of IVIg is associated with significant reduction in SLE disease activity and improvement in complement levels.
    Matched MeSH terms: Models, Statistical
  15. Fulltext A Quantitative Evaluation of Evidence-Based Beliefs and Implementation Among Community Pharmacists: Findings and Impact from United Arab Emirates
    Jairoun AA, Al-Hemyari SS, Shahwan M, El-Dahiyat F, Jairoun M, Al-Tamimi SK, et al.
    Risk Manag Healthc Policy, 2021;14:967-977.
    PMID: 33727873 DOI: 10.2147/RMHP.S283068
    Background: The flux of pharmaceutical data can have a negative impact on the complexity of a pharmacist's decision-making process, which will demand an extensive evaluation from healthcare providers trying to choose the most suitable therapeutic plans for their patients.

    Objective: The current study aimed to assess the beliefs and implementations of community pharmacists in the UAE regarding evidence-based practice (EBP) and to explore the significant factors governing their EBP.

    Setting: Community pharmacies in Dubai and the Northern Emirates, UAE.

    Methods: A descriptive cross-sectional study was conducted over six months between December 2017 and June 2018. Community pharmacists who had three months' professional experience or more and were registered with one of three regulatory bodies (Ministry of Health, Health Authority Abu Dhabi, or Dubai Health Authority) were interviewed by three trained final-year pharmacy students. Face-to-face interviews were then carried out and a structured questionnaire was used.

    Metrics: The average beliefs score was 36% (95% CI: [34%, 39%]) compared to an implementation score of 35% (95% CI: [33%, 37%]).

    Results: A total of 505 subjects participated in the study and completed the entire questionnaire. On average, participants scored higher in beliefs score than implementation score. The results of the statistical modelling showed that younger, female, higher-position pharmacists with more experience and with low percentages of full-time working, and graduates from international/regional universities were more likely to believe in and implement the concept of EBP.

    Conclusion: A gap was identified between the beliefs and implementation of EBP. Developing educational EBP courses in undergraduate pharmacy curricula is of high importance, not only to increase knowledge levels but also to encourage commitment in those pharmacists to strive for professionalism and to support the provided patient care with evidence.

    Matched MeSH terms: Models, Statistical
  16. The combined effect of optimal control and swarm intelligence on optimization of cancer chemotherapy
    Shindi O, Kanesan J, Kendall G, Ramanathan A
    Comput Methods Programs Biomed, 2020 Jun;189:105327.
    PMID: 31978808 DOI: 10.1016/j.cmpb.2020.105327
    BACKGROUND AND OBJECTIVES: In cancer therapy optimization, an optimal amount of drug is determined to not only reduce the tumor size but also to maintain the level of chemo toxicity in the patient's body. The increase in the number of objectives and constraints further burdens the optimization problem. The objective of the present work is to solve a Constrained Multi- Objective Optimization Problem (CMOOP) of the Cancer-Chemotherapy. This optimization results in optimal drug schedule through the minimization of the tumor size and the drug concentration by ensuring the patient's health level during dosing within an acceptable level.

    METHODS: This paper presents two hybrid methodologies that combines optimal control theory with multi-objective swarm and evolutionary algorithms and compares the performance of these methodologies with multi-objective swarm intelligence algorithms such as MOEAD, MODE, MOPSO and M-MOPSO. The hybrid and conventional methodologies are compared by addressing CMOOP.

    RESULTS: The minimized tumor and drug concentration results obtained by the hybrid methodologies demonstrate that they are not only superior to pure swarm intelligence or evolutionary algorithm methodologies but also consumes far less computational time. Further, Second Order Sufficient Condition (SSC) is also used to verify and validate the optimality condition of the constrained multi-objective problem.

    CONCLUSION: The proposed methodologies reduce chemo-medicine administration while maintaining effective tumor killing. This will be helpful for oncologist to discover and find the optimum dose schedule of the chemotherapy that reduces the tumor cells while maintaining the patients' health at a safe level.

    Matched MeSH terms: Models, Statistical
  17. Fulltext Determination of Cutoff Values for the Screening of Osteosarcopenia in Obese Postmenopausal Women
    Abidin NZ, Mitra SR
    Curr Gerontol Geriatr Res, 2021;2021:6634474.
    PMID: 33790963 DOI: 10.1155/2021/6634474
    Osteosarcopenic obesity (OSO) describes the concurrent presence of obesity, low bone mass, and low muscle mass in an individual. Currently, no established criteria exist to diagnose OSO. We hypothesized that obese individuals require different cut-points from standard cut-points to define low bone mass and low muscle mass due to their higher weight load. In this study, we determined cutoff values for the screening of osteosarcopenia (OS) in obese postmenopausal Malaysian women based on the measurements of quantitative ultrasound (QUS), bioelectrical impedance analysis (BIA), and functional performance test. Then, we compared the cutoff values derived by 3 different statistical modeling methods, (1) receiver operating characteristic (ROC) curve, (2) lowest quintile of the study population, and (3) 2 standard deviations (SD) below the mean value of a young reference group, and discussed the most suitable method to screen for the presence of OS in obese population. One hundred and forty-one (n = 141) postmenopausal Malaysian women participated in the study. Bone density was assessed using calcaneal quantitative ultrasound. Body composition was assessed using bioelectrical impedance analyzer. Handgrip strength was assessed using a handgrip dynamometer, and physical performance was assessed using a modified Short Physical Performance Battery test. ROC curve was determined to be the most suitable statistical modeling method to derive the cutoffs for the presence of OS in obese population. From the ROC curve method, the final model to estimate the probability of OS in obese postmenopausal women is comprised of five variables: handgrip strength (HGS, with area under the curve (AUC) = 0.698 and threshold ≤ 16.5 kg), skeletal muscle mass index (SMMI, AUC = 0.966 and threshold ≤ 8.2 kg/m2), fat-free mass index (FFMI, AUC = 0.946 and threshold ≤ 15.2 kg/m2), broadband ultrasonic attenuation (BUA, AUC = 0.987 and threshold ≤ 52.85 dB/MHz), and speed of sound (SOS, AUC = 0.991 and threshold ≤ 1492.15 m/s). Portable equipment may be used to screen for OS in obese women. Early identification of OS can help lower the risk of advanced functional impairment that can lead to physical disability in obese postmenopausal women.
    Matched MeSH terms: Models, Statistical
  18. Fulltext Biodiscovery of Potential Antibacterial Diagnostic Metabolites from the Endolichenic Fungus Xylaria venustula Using LC-MS-Based Metabolomics
    Santiago KAA, Edrada-Ebel R, Dela Cruz TEE, Cheow YL, Ting ASY
    Biology (Basel), 2021 Mar 04;10(3).
    PMID: 33806264 DOI: 10.3390/biology10030191
    Three species of the lichen Usnea (U. baileyi (Stirt.) Zahlbr., U. bismolliuscula Zahlbr. and U. pectinata Stirt.) and nine associated endolichenic fungi (ELF) were evaluated using a metabolomics approach. All investigated lichen crude extracts afforded antibacterial activity against Staphylococcus aureus (minimum inhibitory concentration (MIC): 0.0625 mg/mL), but none was observed against Escherichia coli, while the ELF extract Xylaria venustula was found to be the most active against S. aureus (MIC: 2.5 mg/mL) and E. coli (MIC: 5 mg/mL). X. venustula was fractionated and tested for to determine its antibacterial activity. Fractions XvFr1 to 5 displayed bioactivities against both test bacteria. Selected crude extracts and fractions were subjected to metabolomics analyses using high-resolution LC-MS. Multivariate analyses showed the presence of five secondary metabolites unique to bioactive fractions XvFr1 to 3, which were identified as responsible for the antibacterial activity of X. venustula. The p-values of these metabolites were at the margin of significance level, with methyl xylariate C (P_60) being the most significant. However, their high variable importance of projection (VIP) scores (>5) suggest these metabolites are potential diagnostic metabolites for X. venustula for "dual" bioactivity against S. aureus and E. coli. The statistical models also showed the distinctiveness of metabolites produced by lichens and ELF, thus supporting our hypotheses of ELF functionality similar to plant endophytes.
    Matched MeSH terms: Models, Statistical
  19. Objective assessment of psoriasis erythema for PASI scoring
    Ahmad Fadzil MH, Ihtatho D, Affandi AM, Hussein SH
    Annu Int Conf IEEE Eng Med Biol Soc, 2008;2008:4070-3.
    PMID: 19163606 DOI: 10.1109/IEMBS.2008.4650103
    Skin colour is vital information in dermatological diagnosis. It reflects pathological condition beneath the skin and commonly being used to indicate the extent of a disease. Psoriasis is a skin disease which is indicated by the appearance of red plaques. Although there is no cure for psoriasis, there are many treatment modalities to help control the disease. To evaluate treatment efficacy, PASI (Psoriasis Area and Severity Index) which is the current gold standard method is used to determine severity of psoriasis lesion. Erythema (redness) is one parameter in PASI. Commonly, the erythema is assessed visually, thus leading to subjective and inconsistent result. In this work, we proposed an objective assessment of psoriasis erythema for PASI scoring. The colour of psoriasis lesion is analyzed by DeltaL, Deltahue, and Deltachroma of CIELAB colour space. References of lesion with different scores are obtained from the selected lesions by two dermatologists. Results based on 38 lesions from 22 patients with various level of skin pigmentation show that PASI erythema score can be determined objectively and consistent with dermatology scoring.
    Matched MeSH terms: Models, Statistical
  20. Fulltext The applicability of social cognitive career theory in predicting life satisfaction of university students: A meta-analytic path analysis
    Mohd Rasdi R, Ahrari S
    PLoS One, 2020;15(8):e0237838.
    PMID: 32822400 DOI: 10.1371/journal.pone.0237838
    Derived from the social cognitive career theory (SCCT), the present study developed a model for the empirical examination of factors affecting the life satisfaction of university students. A random-effects meta-analysis of zero-order correlations observed the results of 16 studies (20 samples, n = 7,967), and associations among the SCCT variables were examined by using a meta-analytic structural equation modeling (MASEM) according to a pooled correlation matrix. An alternative model was offered and then assessed. The findings showed a satisfactory fit of the new model as compared to the original SCCT. The results demonstrated support for the alternative model of SCCT in predicting life satisfaction. The present study suggested that researchers should embrace this alternative model when synthesizing SCCT factors. Limitations and avenues for future research were put forward for further consideration.
    Matched MeSH terms: Models, Statistical
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