Displaying publications 41 - 51 of 51 in total

Abstract:
Sort:
  1. Nazeri M, Jusoff K, Madani N, Mahmud AR, Bahman AR, Kumar L
    PLoS One, 2012;7(10):e48104.
    PMID: 23110182 DOI: 10.1371/journal.pone.0048104
    One of the available tools for mapping the geographical distribution and potential suitable habitats is species distribution models. These techniques are very helpful for finding poorly known distributions of species in poorly sampled areas, such as the tropics. Maximum Entropy (MaxEnt) is a recently developed modeling method that can be successfully calibrated using a relatively small number of records. In this research, the MaxEnt model was applied to describe the distribution and identify the key factors shaping the potential distribution of the vulnerable Malayan Sun Bear (Helarctos malayanus) in one of the main remaining habitats in Peninsular Malaysia. MaxEnt results showed that even though Malaysian sun bear habitat is tied with tropical evergreen forests, it lives in a marginal threshold of bio-climatic variables. On the other hand, current protected area networks within Peninsular Malaysia do not cover most of the sun bears potential suitable habitats. Assuming that the predicted suitability map covers sun bears actual distribution, future climate change, forest degradation and illegal hunting could potentially severely affect the sun bear's population.
    Matched MeSH terms: Entropy
  2. Tayyab S, Zaroog MS, Feroz SR, Mohamad SB, Malek SN
    Int J Pharm, 2015 Aug 1;491(1-2):352-8.
    PMID: 26142245 DOI: 10.1016/j.ijpharm.2015.06.042
    The interaction of tranilast (TRN), an antiallergic drug with the main drug transporter in human circulation, human serum albumin (HSA) was studied using isothermal titration calorimetry (ITC), fluorescence spectroscopy and in silico docking methods. ITC data revealed the binding constant and stoichiometry of binding as (3.21 ± 0.23) × 10(6)M(-1) and 0.80 ± 0.08, respectively, at 25°C. The values of the standard enthalpy change (ΔH°) and the standard entropy change (ΔS°) for the interaction were found as -25.2 ± 5.1 kJ mol(-1) and 46.9 ± 5.4 J mol(-1)K(-1), respectively. Both thermodynamic data and modeling results suggested the involvement of hydrogen bonding, hydrophobic and van der Waals forces in the complex formation. Three-dimensional fluorescence data of TRN-HSA complex demonstrated significant changes in the microenvironment around the protein fluorophores upon drug binding. Competitive drug displacement results as well as modeling data concluded the preferred binding site of TRN as Sudlow's site I on HSA.
    Matched MeSH terms: Entropy
  3. Namazi H, Akrami A, Nazeri S, Kulish VV
    Biomed Res Int, 2016;2016:5469587.
    PMID: 27699169
    An important challenge in brain research is to make out the relation between the features of olfactory stimuli and the electroencephalogram (EEG) signal. Yet, no one has discovered any relation between the structures of olfactory stimuli and the EEG signal. This study investigates the relation between the structures of EEG signal and the olfactory stimulus (odorant). We show that the complexity of the EEG signal is coupled with the molecular complexity of the odorant, where more structurally complex odorant causes less fractal EEG signal. Also, odorant having higher entropy causes the EEG signal to have lower approximate entropy. The method discussed here can be applied and investigated in case of patients with brain diseases as the rehabilitation purpose.
    Matched MeSH terms: Entropy
  4. Aimie-Salleh N, Malarvili MB, Whittaker AC
    Med Biol Eng Comput, 2019 Jun;57(6):1229-1245.
    PMID: 30734153 DOI: 10.1007/s11517-019-01958-3
    Adverse childhood experiences have been suggested to cause changes in physiological processes and can determine the magnitude of the stress response which might have a significant impact on health later in life. To detect the stress response, biomarkers that represent both the Autonomic Nervous System (ANS) and Hypothalamic-Pituitary-Adrenal (HPA) axis are proposed. Among the available biomarkers, Heart Rate Variability (HRV) has been proven as a powerful biomarker that represents ANS. Meanwhile, salivary cortisol has been suggested as a biomarker that reflects the HPA axis. Even though many studies used multiple biomarkers to measure the stress response, the results for each biomarker were analyzed separately. Therefore, the objective of this study is to propose a fusion of ANS and HPA axis biomarkers in order to classify the stress response based on adverse childhood experience. Electrocardiograph, blood pressure (BP), pulse rate (PR), and salivary cortisol (SCort) measures were collected from 23 healthy participants; 11 participants had adverse childhood experience while the remaining 12 acted as the no adversity control group. HRV was then computed from the ECG and the HRV features were extracted. Next, the selected HRV features were combined with the other biomarkers using Euclidean distance (ed) and serial fusion, and the performance of the fused features was compared using Support Vector Machine. From the result, HRV-SCort using Euclidean distance achieved the most satisfactory performance with 80.0% accuracy, 83.3% sensitivity, and 78.3% specificity. Furthermore, the performance of the stress response classification of the fused biomarker, HRV-SCort, outperformed that of the single biomarkers: HRV (61% Accuracy), Cort (59.4% Accuracy), BP (78.3% accuracy), and PR (53.3% accuracy). From this study, it was proven that the fused biomarkers that represent both ANS and HPA (HRV-SCort) able to demonstrate a better classification performance in discriminating the stress response. Furthermore, a new approach for classification of stress response using Euclidean distance and SVM named as ed-SVM was proven to be an effective method for the HRV-SCort in classifying the stress response from PASAT. The robustness of this method is crucial in contributing to the effectiveness of the stress response measures and could further be used as an indicator for future health. Graphical abstract ᅟ.
    Matched MeSH terms: Entropy
  5. Abd Raman HS, Tan S, August JT, Khan AM
    PeerJ, 2020;7:e7954.
    PMID: 32518710 DOI: 10.7717/peerj.7954
    Background: Influenza A (H5N1) virus is a global concern with potential as a pandemic threat. High sequence variability of influenza A viruses is a major challenge for effective vaccine design. A continuing goal towards this is a greater understanding of influenza A (H5N1) proteome sequence diversity in the context of the immune system (antigenic diversity), the dynamics of mutation, and effective strategies to overcome the diversity for vaccine design.

    Methods: Herein, we report a comprehensive study of the dynamics of H5N1 mutations by analysis of the aligned overlapping nonamer positions (1-9, 2-10, etc.) of more than 13,000 protein sequences of avian and human influenza A (H5N1) viruses, reported over at least 50 years. Entropy calculations were performed on 9,408 overlapping nonamer position of the proteome to study the diversity in the context of immune system. The nonamers represent the predominant length of the binding cores for peptides recognized by the cellular immune system. To further dissect the sequence diversity, each overlapping nonamer position was quantitatively analyzed for four patterns of sequence diversity motifs: index, major, minor and unique.

    Results: Almost all of the aligned overlapping nonamer positions of each viral proteome exhibited variants (major, minor, and unique) to the predominant index sequence. Each variant motif displayed a characteristic pattern of incidence change in relation to increased total variants. The major variant exhibited a restrictive pyramidal incidence pattern, with peak incidence at 50% total variants. Post this peak incidence, the minor variants became the predominant motif for majority of the positions. Unique variants, each sequence observed only once, were present at nearly all of the nonamer positions. The diversity motifs (index and variants) demonstrated complex inter-relationships, with motif switching being a common phenomenon. Additionally, 25 highly conserved sequences were identified to be shared across viruses of both hosts, with half conserved to several other influenza A subtypes.

    Discussion: The presence of distinct sequences (nonatypes) at nearly all nonamer positions represents a large repertoire of reported viral variants in the proteome, which influence the variability dynamics of the viral population. This work elucidated and provided important insights on the components that make up the viral diversity, delineating inherent patterns in the organization of sequence changes that function in the viral fitness-selection. Additionally, it provides a catalogue of all the mutational changes involved in the dynamics of H5N1 viral diversity for both avian and human host populations. This work provides data relevant for the design of prophylactics and therapeutics that overcome the diversity of the virus, and can aid in the surveillance of existing and future strains of influenza viruses.

    Matched MeSH terms: Entropy
  6. Acharya UR, Raghavendra U, Fujita H, Hagiwara Y, Koh JE, Jen Hong T, et al.
    Comput Biol Med, 2016 12 01;79:250-258.
    PMID: 27825038 DOI: 10.1016/j.compbiomed.2016.10.022
    Fatty liver disease (FLD) is reversible disease and can be treated, if it is identified at an early stage. However, if diagnosed at the later stage, it can progress to an advanced liver disease such as cirrhosis which may ultimately lead to death. Therefore, it is essential to detect it at an early stage before the disease progresses to an irreversible stage. Several non-invasive computer-aided techniques are proposed to assist in the early detection of FLD and cirrhosis using ultrasound images. In this work, we are proposing an algorithm to discriminate automatically the normal, FLD and cirrhosis ultrasound images using curvelet transform (CT) method. Higher order spectra (HOS) bispectrum, HOS phase, fuzzy, Kapoor, max, Renyi, Shannon, Vajda and Yager entropies are extracted from CT coefficients. These extracted features are subjected to locality sensitive discriminant analysis (LSDA) feature reduction method. Then these LSDA coefficients ranked based on F-value are fed to different classifiers to choose the best performing classifier using minimum number of features. Our proposed technique can characterize normal, FLD and cirrhosis using probabilistic neural network (PNN) classifier with an accuracy of 97.33%, specificity of 100.00% and sensitivity of 96.00% using only six features. In addition, these chosen features are used to develop a liver disease index (LDI) to differentiate the normal, FLD and cirrhosis classes using a single number. This can significantly help the radiologists to discriminate FLD and cirrhosis in their routine liver screening.
    Matched MeSH terms: Entropy
  7. Muhamad MAH, Che Hasan R, Md Said N, Ooi JL
    PLoS One, 2021;16(9):e0257761.
    PMID: 34555110 DOI: 10.1371/journal.pone.0257761
    Integrating Multibeam Echosounder (MBES) data (bathymetry and backscatter) and underwater video technology allows scientists to study marine habitats. However, use of such data in modeling suitable seagrass habitats in Malaysian coastal waters is still limited. This study tested multiple spatial resolutions (1 and 50 m) and analysis window sizes (3 × 3, 9 × 9, and 21 × 21 cells) probably suitable for seagrass-habitat relationships in Redang Marine Park, Terengganu, Malaysia. A maximum entropy algorithm was applied, using 12 bathymetric and backscatter predictors to develop a total of 6 seagrass habitat suitability models. The results indicated that both fine and coarse spatial resolution datasets could produce models with high accuracy (>90%). However, the models derived from the coarser resolution dataset displayed inconsistent habitat suitability maps for different analysis window sizes. In contrast, habitat models derived from the fine resolution dataset exhibited similar habitat distribution patterns for three different analysis window sizes. Bathymetry was found to be the most influential predictor in all the models. The backscatter predictors, such as angular range analysis inversion parameters (characterization and grain size), gray-level co-occurrence texture predictors, and backscatter intensity levels, were more important for coarse resolution models. Areas of highest habitat suitability for seagrass were predicted to be in shallower (<20 m) waters and scattered between fringing reefs (east to south). Some fragmented, highly suitable habitats were also identified in the shallower (<20 m) areas in the northwest of the prediction models and scattered between fringing reefs. This study highlighted the importance of investigating the suitable spatial resolution and analysis window size of predictors from MBES for modeling suitable seagrass habitats. The findings provide important insight on the use of remote acoustic sonar data to study and map seagrass distribution in Malaysia coastal water.
    Matched MeSH terms: Entropy
  8. Olusesan AT, Azura LK, Forghani B, Bakar FA, Mohamed AK, Radu S, et al.
    N Biotechnol, 2011 Oct;28(6):738-45.
    PMID: 21238617 DOI: 10.1016/j.nbt.2011.01.002
    Thermostable lipase produced by a genotypically identified extremophilic Bacillus subtilis NS 8 was purified 500-fold to homogeneity with a recovery of 16% by ultrafiltration, DEAE-Toyopearl 650M and Sephadex G-75 column. The purified enzyme showed a prominent single band with a molecular weight of 45 kDa. The optimum pH and temperature for activity of lipase were 7.0 and 60°C, respectively. The enzyme was stable in the pH range between 7.0 and 9.0 and temperature range between 40 and 70°C. It showed high stability with half-lives of 273.38 min at 60°C, 51.04 min at 70°C and 41.58 min at 80°C. The D-values at 60, 70 and 80°C were 788.70, 169.59 and 138.15 min, respectively. The enzyme's enthalpy, entropy and Gibb's free energy were in the range of 70.07-70.40 kJ mol(-1), -83.58 to -77.32 kJ mol(-1)K(-1) and 95.60-98.96 kJ mol(-1), respectively. Lipase activity was slightly enhanced when treated with Mg(2+) but there was no significant enhancement or inhibition of the activity with Ca(2+). However, other metal ions markedly inhibited its activity. Of all the natural vegetable oils tested, it had slightly higher hydrolytic activity on soybean oil compared to other oils. On TLC plate, the enzyme showed non-regioselective activity for triolein hydrolysis.
    Matched MeSH terms: Entropy
  9. Al-Qazzaz NK, Ali SHBM, Ahmad SA, Islam MS, Escudero J
    Med Biol Eng Comput, 2018 Jan;56(1):137-157.
    PMID: 29119540 DOI: 10.1007/s11517-017-1734-7
    Stroke survivors are more prone to developing cognitive impairment and dementia. Dementia detection is a challenge for supporting personalized healthcare. This study analyzes the electroencephalogram (EEG) background activity of 5 vascular dementia (VaD) patients, 15 stroke-related patients with mild cognitive impairment (MCI), and 15 control healthy subjects during a working memory (WM) task. The objective of this study is twofold. First, it aims to enhance the discrimination of VaD, stroke-related MCI patients, and control subjects using fuzzy neighborhood preserving analysis with QR-decomposition (FNPAQR); second, it aims to extract and investigate the spectral features that characterize the post-stroke dementia patients compared to the control subjects. Nineteen channels were recorded and analyzed using the independent component analysis and wavelet analysis (ICA-WT) denoising technique. Using ANOVA, linear spectral power including relative powers (RP) and power ratio were calculated to test whether the EEG dominant frequencies were slowed down in VaD and stroke-related MCI patients. Non-linear features including permutation entropy (PerEn) and fractal dimension (FD) were used to test the degree of irregularity and complexity, which was significantly lower in patients with VaD and stroke-related MCI than that in control subjects (ANOVA; p ˂ 0.05). This study is the first to use fuzzy neighborhood preserving analysis with QR-decomposition (FNPAQR) dimensionality reduction technique with EEG background activity of dementia patients. The impairment of post-stroke patients was detected using support vector machine (SVM) and k-nearest neighbors (kNN) classifiers. A comparative study has been performed to check the effectiveness of using FNPAQR dimensionality reduction technique with the SVM and kNN classifiers. FNPAQR with SVM and kNN obtained 91.48 and 89.63% accuracy, respectively, whereas without using the FNPAQR exhibited 70 and 67.78% accuracy for SVM and kNN, respectively, in classifying VaD, stroke-related MCI, and control patients, respectively. Therefore, EEG could be a reliable index for inspecting concise markers that are sensitive to VaD and stroke-related MCI patients compared to control healthy subjects.
    Matched MeSH terms: Entropy
  10. Wong YM, Show PL, Wu TY, Leong HY, Ibrahim S, Juan JC
    J Biosci Bioeng, 2019 Feb;127(2):150-159.
    PMID: 30224189 DOI: 10.1016/j.jbiosc.2018.07.012
    Bio-hydrogen production from wastewater using sludge as inoculum is a sustainable approach for energy production. This study investigated the influence of initial pH and temperature on bio-hydrogen production from dairy wastewater using pretreated landfill leachate sludge (LLS) as an inoculum. The maximum yield of 113.2 ± 2.9 mmol H2/g chemical oxygen demand (COD) (12.8 ± 0.3 mmol H2/g carbohydrates) was obtained at initial pH 6 and 37 °C. The main products of volatile fatty acids were acetate and butyrate with the ratio of acetate:butyrate was 0.4. At optimum condition, Gibb's free energy was estimated at -40 kJ/mol, whereas the activation enthalpy and entropy were 65 kJ/mol and 0.128 kJ/mol/l, respectively. These thermodynamic quantities suggest that bio-hydrogen production from dairy wastewater using pretreated LLS as inoculum was effective and efficient. In addition, genomic and bioinformatics analyses were performed in this study.
    Matched MeSH terms: Entropy
  11. Abas FS, Shana'ah A, Christian B, Hasserjian R, Louissaint A, Pennell M, et al.
    Cytometry A, 2017 06;91(6):609-621.
    PMID: 28110507 DOI: 10.1002/cyto.a.23049
    The advance of high resolution digital scans of pathology slides allowed development of computer based image analysis algorithms that may help pathologists in IHC stains quantification. While very promising, these methods require further refinement before they are implemented in routine clinical setting. Particularly critical is to evaluate algorithm performance in a setting similar to current clinical practice. In this article, we present a pilot study that evaluates the use of a computerized cell quantification method in the clinical estimation of CD3 positive (CD3+) T cells in follicular lymphoma (FL). Our goal is to demonstrate the degree to which computerized quantification is comparable to the practice of estimation by a panel of expert pathologists. The computerized quantification method uses entropy based histogram thresholding to separate brown (CD3+) and blue (CD3-) regions after a color space transformation. A panel of four board-certified hematopathologists evaluated a database of 20 FL images using two different reading methods: visual estimation and manual marking of each CD3+ cell in the images. These image data and the readings provided a reference standard and the range of variability among readers. Sensitivity and specificity measures of the computer's segmentation of CD3+ and CD- T cell are recorded. For all four pathologists, mean sensitivity and specificity measures are 90.97 and 88.38%, respectively. The computerized quantification method agrees more with the manual cell marking as compared to the visual estimations. Statistical comparison between the computerized quantification method and the pathologist readings demonstrated good agreement with correlation coefficient values of 0.81 and 0.96 in terms of Lin's concordance correlation and Spearman's correlation coefficient, respectively. These values are higher than most of those calculated among the pathologists. In the future, the computerized quantification method may be used to investigate the relationship between the overall architectural pattern (i.e., interfollicular vs. follicular) and outcome measures (e.g., overall survival, and time to treatment). © 2017 International Society for Advancement of Cytometry.
    Matched MeSH terms: Entropy
Related Terms
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links