Displaying publications 21 - 40 of 106 in total

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  1. Discrimination of stroke-related mild cognitive impairment and vascular dementia using EEG signal analysis
    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.
  2. Fulltext Complexity and Entropy Analysis to Improve Gender Identification from Emotional-Based EEGs
    Al-Qazzaz NK, Sabir MK, Bin Mohd Ali SH, Ahmad SA, Grammer K
    J Healthc Eng, 2021;2021:8537000.
    PMID: 34603651 DOI: 10.1155/2021/8537000
    Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent (Hur) and amplitude-aware permutation entropy (AAPE) features were extracted from the EEG dataset. k-nearest neighbors (kNN) and support vector machine (SVM) classification techniques were considered for automatic gender recognition from emotional-based EEGs. The main novelty of this paper is twofold: first, to investigate Hur as a complexity feature and AAPE as an irregularity parameter for the emotional-based EEGs using two-way analysis of variance (ANOVA) and then integrating these features to propose a new CompEn hybrid feature fusion method towards developing the novel WT_CompEn gender recognition framework as a core for an automated gender recognition model to be sensitive for identifying gender roles in the brain-emotion relationship for females and males. The results illustrated the effectiveness of Hur and AAPE features as remarkable indices for investigating gender-based anger, sadness, happiness, and neutral emotional state. Moreover, the proposed WT_CompEn framework achieved significant enhancement in SVM classification accuracy of 100%, indicating that the novel WT_CompEn may offer a useful way for reliable enhancement of gender recognition of different emotional states. Therefore, the novel WT_CompEn framework is a crucial goal for improving the process of automatic gender recognition from emotional-based EEG signals allowing for more comprehensive insights to understand various gender differences and human behavior effects of an intervention on the brain.
  3. Classification of ankle joint movements based on surface electromyography signals for rehabilitation robot applications
    Al-Quraishi MS, Ishak AJ, Ahmad SA, Hasan MK, Al-Qurishi M, Ghapanchizadeh H, et al.
    Med Biol Eng Comput, 2017 May;55(5):747-758.
    PMID: 27484411 DOI: 10.1007/s11517-016-1551-4
    Electromyography (EMG)-based control is the core of prostheses, orthoses, and other rehabilitation devices in recent research. Nonetheless, EMG is difficult to use as a control signal given the complex nature of the signal. To overcome this problem, the researchers employed a pattern recognition technique. EMG pattern recognition mainly involves four stages: signal detection, preprocessing feature extraction, dimensionality reduction, and classification. In particular, the success of any pattern recognition technique depends on the feature extraction stage. In this study, a modified time-domain features set and logarithmic transferred time-domain features (LTD) were evaluated and compared with other traditional time-domain features set (TTD). Three classifiers were employed to assess the two feature sets, namely linear discriminant analysis (LDA), k nearest neighborhood, and Naïve Bayes. Results indicated the superiority of the new time-domain feature set LTD, on conventional time-domain features TTD with the average classification accuracy of 97.23 %. In addition, the LDA classifier outperformed the other two classifiers considered in this study.
  4. Fulltext Rhizodegradation of Petroleum Oily Sludge-contaminated Soil Using Cajanus cajan Increases the Diversity of Soil Microbial Community
    Allamin IA, Halmi MIE, Yasid NA, Ahmad SA, Abdullah SRS, Shukor Y
    Sci Rep, 2020 Mar 05;10(1):4094.
    PMID: 32139706 DOI: 10.1038/s41598-020-60668-1
    Most components of petroleum oily sludge (POS) are toxic, mutagenic and cancer-causing. Often bioremediation using microorganisms is hindered by the toxicity of POS. Under this circumstance, phytoremediation is the main option as it can overcome the toxicity of POS. Cajanus cajan a legume plant, was evaluated as a phyto-remediating agent for petroleum oily sludge-spiked soil. Culture dependent and independent methods were used to determine the rhizosphere microorganisms' composition. Degradation rates were estimated gravimetrically. The population of total heterotrophic bacteria (THRB) was significantly higher in the uncontaminated soil compared to the contaminated rhizosphere soil with C. cajan, but the population of hydrocarbon-utilizing bacteria (HUB) was higher in the contaminated rhizosphere soil. The results show that for 1 to 3% oily sludge concentrations, an increase in microbial counts for all treatments from day 0 to 90 d was observed with the contaminated rhizosphere CR showing the highest significant increase (p  
  5. Fulltext Self-Calibration Algorithm for a Pressure Sensor with a Real-Time Approach Based on an Artificial Neural Network
    Almassri AMM, Wan Hasan WZ, Ahmad SA, Shafie S, Wada C, Horio K
    Sensors (Basel), 2018 Aug 05;18(8).
    PMID: 30081581 DOI: 10.3390/s18082561
    This paper presents a novel approach to predicting self-calibration in a pressure sensor using a proposed Levenberg Marquardt Back Propagation Artificial Neural Network (LMBP-ANN) model. The self-calibration algorithm should be able to fix major problems in the pressure sensor such as hysteresis, variation in gain and lack of linearity with high accuracy. The traditional calibration process for this kind of sensor is a time-consuming task because it is usually done through manual and repetitive identification. Furthermore, a traditional computational method is inadequate for solving the problem since it is extremely difficult to resolve the mathematical formula among multiple confounding pressure variables. Accordingly, this paper describes a new self-calibration methodology for nonlinear pressure sensors based on an LMBP-ANN model. The proposed method was achieved using a collected dataset from pressure sensors in real time. The load cell will be used as a reference for measuring the applied force. The proposed method was validated by comparing the output pressure of the trained network with the experimental target pressure (reference). This paper also shows that the proposed model exhibited a remarkable performance than traditional methods with a max mean square error of 0.17325 and an R-value over 0.99 for the total response of training, testing and validation. To verify the proposed model's capability to build a self-calibration algorithm, the model was tested using an untrained input data set. As a result, the proposed LMBP-ANN model for self-calibration purposes is able to successfully predict the desired pressure over time, even the uncertain behaviour of the pressure sensors due to its material creep. This means that the proposed model overcomes the problems of hysteresis, variation in gain and lack of linearity over time. In return, this can be used to enhance the durability of the grasping mechanism, leading to a more robust and secure grasp for paralyzed hands. Furthermore, the exposed analysis approach in this paper can be a useful methodology for the user to evaluate the performance of any measurement system in a real-time environment.
  6. Isolation and characterization of a phenol-degrading Rhodococcus sp. strain AQ5NOL 2 KCTC 11961BP
    Arif NM, Ahmad SA, Syed MA, Shukor MY
    J Basic Microbiol, 2013 Jan;53(1):9-19.
    PMID: 22581645 DOI: 10.1002/jobm.201100120
    In this work, we report on the isolation of a phenol-degrading Rhodococcus sp. with a high tolerance towards phenol. The isolate was identified as Rhodococcus sp. strain AQ5NOL 2, based on 16S rDNA analysis. The strain degraded phenol using the meta pathway, a trait shared by many phenol-degraders. In addition to phenol biodegradation, the strain was also capable of degrading diesel. Strain AQ5NOL 2 exhibited a broad optimum temperature for growth on phenol at between 20 °C and 35 °C. The best nitrogen sources were ammonium sulphate, glycine or phenylalanine, followed by proline, nitrate, leucine, and alanine (in decreasing efficiency). Strain AQ5NOL 2 showed a high tolerance and degradation capacity of phenol, for it was able to register growth in the presence of 2000 mg l(-1) phenol. The growth of this strain on phenol as sole carbon and energy source were modeled using Haldane kinetics with a maximal specific growth rate (μ(max)) of 0.1102 hr(-1), a half-saturation constant (K(s) ) of 99.03 mg l(-1) or 1.05 mmol l(-1), and a substrate inhibition constant (K(i)) of 354 mg l(-1) or 3.76 mmol l(-1). Aside from phenol, the strain could utilize diesel, 2,4-dinitrophenol and ρ-cresol as carbon sources for growth. Strain AQ5NOL 2 exhibited inhibition of phenol degradation by Zn(2+), Cu(2+), Cr(6+), Ag(+) and Hg(2+) at 1 mg l(-1).
  7. Fulltext Enhancement the electrochemical conductivity of a modified reduced graphene oxide/calixarene screen-printed electrode using response surface methodology
    Azman NZM, Zainal PNS, Alang Ahmad SA
    PLoS One, 2020;15(6):e0234148.
    PMID: 32502185 DOI: 10.1371/journal.pone.0234148
    In this paper, Response Surface Methodology with central composite design (RSM/CCD) was used to optimize a modified electrode for improved electron transfer rate and electrochemical performance. The modification was done on a screen-printed carbon electrode (SPCE) with reduced graphene oxide (ERGO)/calix [4] arene (ERGOC4-SPCE). The properties of the modified electrodes were analyzed via cyclic voltammetry, Raman spectroscopy, and Fourier-Transform Infrared (FT-IR) spectroscopy. Then, different variables were optimized, namely, the concentration of graphene oxide, GO (A), the number of scan cycles of graphene oxide (B), and the deposition time (C). The effect of the optimized variables on the reduction-oxidation peak current response of the potassium ferricyanide redox system was analyzed. By using statistical analysis, it shows a significant effect of the concentration of GO, the deposition time, and the number of scans cycles on the peak current response. The coefficient of determination (R2) value of 0.9987 produced indicated a good fit of the model with experimental finding.
  8. In vivo and in vitro effects on cholinesterase of blood of Oreochromis mossambicus by copper
    Basirun AA, Ahmad SA, Sabullah MK, Yasid NA, Daud HM, Khalid A, et al.
    3 Biotech, 2019 Feb;9(2):64.
    PMID: 30729088 DOI: 10.1007/s13205-019-1592-0
    The present study is aimed to evaluate the effects of sub-acute toxicity testing of copper sulphate (CuSO4), on behavioural, histological and biochemical changes of the Oreochromis mossambicus (black tilapia) blood tissues. The effects were assessed according to the previous results on sub-acute toxicity test after exposing fish to several concentrations (0.0, 2.5, 5.0, and 10.0 mg/L). The observations of scanning electron microscope, and transmission electron microscope studies revealed severe histopathological changes on the surface and the cellular changes in blood tissues, respectively. The morphological alterations in blood involved irregular structure of red blood cell and blood clot formation. CuSO4 affected the biochemical alteration of the blood cholinesterase also known as serum cholinesterase (ChE). Blood ChE inhibited up to 80% of activity when exposed to 10.0 mg/L CuSO4. The findings from this study can further improve the quality standards of aquaculture industry and the fundamental basis in selecting suitable strains among freshwater fish species to be used as bioindicator.
  9. Fulltext HMG-CoA reductase inhibitory activity and phytocomponent investigation of Basella alba leaf extract as a treatment for hypercholesterolemia
    Baskaran G, Salvamani S, Ahmad SA, Shaharuddin NA, Pattiram PD, Shukor MY
    Drug Des Devel Ther, 2015;9:509-17.
    PMID: 25609924 DOI: 10.2147/DDDT.S75056
    The enzyme 3-hydroxy-3-methyl-glutaryl-coenzyme A (HMG-CoA) reductase is the key enzyme of the mevalonate pathway that produces cholesterol. Inhibition of HMG-CoA reductase reduces cholesterol biosynthesis in the liver. Synthetic drugs, statins, are commonly used for the treatment of hypercholesterolemia. Due to the side effects of statins, natural HMG-CoA reductase inhibitors of plant origin are needed. In this study, 25 medicinal plant methanol extracts were screened for anti-HMG-CoA reductase activity. Basella alba leaf extract showed the highest inhibitory effect at about 74%. Thus, B. alba was examined in order to investigate its phytochemical components. Gas chromatography with tandem mass spectrometry and reversed phase high-performance liquid chromatography analysis revealed the presence of phenol 2,6-bis(1,1-dimethylethyl), 1-heptatriacotanol, oleic acid, eicosyl ester, naringin, apigenin, luteolin, ascorbic acid, and α-tocopherol, which have been reported to possess antihypercholesterolemic effects. Further investigation of in vivo models should be performed in order to confirm its potential as an alternative treatment for hypercholesterolemia and related cardiovascular diseases.
  10. Fulltext Hypocholesterolemic and Antiatherosclerotic Potential of Basella alba Leaf Extract in Hypercholesterolemia-Induced Rabbits
    Baskaran G, Salvamani S, Azlan A, Ahmad SA, Yeap SK, Shukor MY
    Evid Based Complement Alternat Med, 2015;2015:751714.
    PMID: 26697097 DOI: 10.1155/2015/751714
    Hypercholesterolemia is the major risk factor that leads to atherosclerosis. Nowadays, alternative treatment using medicinal plants gained much attention since the usage of statins leads to adverse health effects, especially liver and muscle toxicity. This study was designed to investigate the hypocholesterolemic and antiatherosclerotic effects of Basella alba (B. alba) using hypercholesterolemia-induced rabbits. Twenty New Zealand white rabbits were divided into 5 groups and fed with varying diets: normal diet, 2% high cholesterol diet (HCD), 2% HCD + 10 mg/kg simvastatin, 2% HCD + 100 mg/kg B. alba extract, and 2% HCD + 200 mg/kg B. alba extract, respectively. The treatment with B. alba extract significantly lowered the levels of total cholesterol, LDL, and triglycerides and increased HDL and antioxidant enzymes (SOD and GPx) levels. The elevated levels of liver enzymes (AST and ALT) and creatine kinase were noted in hypercholesterolemic and statin treated groups indicating liver and muscle injuries. Treatment with B. alba extract also significantly suppressed the aortic plaque formation and reduced the intima: media ratio as observed in simvastatin-treated group. This is the first in vivo study on B. alba that suggests its potential as an alternative therapeutic agent for hypercholesterolemia and atherosclerosis.
  11. Characterization of surface electromyography using time domain features for determining hand motion and stages of contraction
    Bin Ahmad Nadzri AA, Ahmad SA, Marhaban MH, Jaafar H
    Australas Phys Eng Sci Med, 2014 Mar;37(1):133-7.
    PMID: 24443218 DOI: 10.1007/s13246-014-0243-3
    Surface electromyography (SEMG) signals can provide important information for prosthetic hand control application. In this study, time domain (TD) features were used in extracting information from the SEMG signal in determining hand motions and stages of contraction (start, middle and end). Data were collected from ten healthy subjects. Two muscles, which are flexor carpi ulnaris (FCU) and extensor carpi radialis (ECR) were assessed during three hand motions of wrist flexion (WF), wrist extension (WE) and co-contraction (CC). The SEMG signals were first segmented into 132.5 ms windows, full wave rectified and filtered with a 6 Hz low pass Butterworth filter. Five TD features of mean absolute value, variance, root mean square, integrated absolute value and waveform length were used for feature extraction and subsequently patterns were determined. It is concluded that the TD features that were used are able to differentiate hand motions. However, for the stages of contraction determination, although there were patterns observed, it is determined that the stages could not be properly be differentiated due to the variability of signal strengths between subjects.
  12. Chicken feather valorization by thermal alkaline pretreatment followed by enzymatic hydrolysis for protein-rich hydrolysate production
    Cheong CW, Lee YS, Ahmad SA, Ooi PT, Phang LY
    Waste Manag, 2018 Sep;79:658-666.
    PMID: 30343798 DOI: 10.1016/j.wasman.2018.08.029
    A huge amount of feathers is generated as a waste every year. Feathers can be a protein source if it is treated with an appropriate method. The present study investigates feasibility of autoclave alkaline and microwave alkaline pretreatments to be combined with enzymatic treatment for feather solubilization and protein production. Hydrolysis of chicken feather by autoclave alkaline pretreatment followed by an enzymatic method (AAS) or microwave alkaline pretreatment followed by an enzymatic method (MAS) was optimized by response surface methodology. Various NaOH concentrations for autoclave alkaline pretreatment (0.01-0.1 M) and microwave-alkaline pretreatment (0.01-0.05 M) were applied. The holding time for both pretreatments ranged from 1 to 10 min. The pretreated feathers were subjected to enzymatic hydrolysis using a commercial enzyme prior to analysis of protein content, feather solubilization, functional groups, and elemental composition (carbon, hydrogen, nitrogen and sulfur) of the treated feathers. The results revealed that both autoclave alkaline pretreatment and microwave alkaline pretreatment under optimized conditions of 0.068 M NaOH, 2 min holding time, 105 °C and 450 W, 0.05 M NaOH for 10 min, respectively, enhanced the subsequent Savinase hydrolysis of chicken feathers to achieve more than 80% degradation and more than 70% protein recovery. Fourier transform infrared spectroscopy results showed that both thermal-alkaline pretreatments weakened the structure of the feather. Reduction of carbon, nitrogen, and sulfur occurred in both thermal-alkaline pretreatments of feathers indicating degradation of the feather as well as protein release. Thermal-alkaline pretreatment may be a promising method for enhancing the enzymatic hydrolysis of chicken feathers and for producing a protein-rich hydrolysate.
  13. A proposed aerobic granules size development scheme for aerobic granulation process
    Dahalan FA, Abdullah N, Yuzir A, Olsson G, Salmiati, Hamdzah M, et al.
    Bioresour Technol, 2015 Apr;181:291-6.
    PMID: 25661308 DOI: 10.1016/j.biortech.2015.01.062
    Aerobic granulation is increasingly used in wastewater treatment due to its unique physical properties and microbial functionalities. Granule size defines the physical properties of granules based on biomass accumulation. This study aims to determine the profile of size development under two physicochemical conditions. Two identical bioreactors namely Rnp and Rp were operated under non-phototrophic and phototrophic conditions, respectively. An illustrative scheme was developed to comprehend the mechanism of size development that delineates the granular size throughout the granulation. Observations on granules' size variation have shown that activated sludge revolutionised into the form of aerobic granules through the increase of biomass concentration in bioreactors which also determined the changes of granule size. Both reactors demonstrated that size transformed in a similar trend when tested with and without illumination. Thus, different types of aerobic granules may increase in size in the same way as recommended in the aerobic granule size development scheme.
  14. Fulltext Antarctic heavy metal pollution and remediation efforts: state of the art of research and scientific publications
    Darham S, Zakaria NN, Zulkharnain A, Sabri S, Khalil KA, Merican F, et al.
    Braz J Microbiol, 2023 Sep;54(3):2011-2026.
    PMID: 36973583 DOI: 10.1007/s42770-023-00949-9
    In Antarctica, human activities have been reported to be the major cause of the accumulation of heavy metal contaminants. A comprehensive bibliometric analysis of publications on heavy metal contamination in Antarctica from year 2000 to 2020 was performed to obtain an overview of the current landscape in this line of research. A total of 106 documents were obtained from Scopus, the largest citation database. Extracted data were analysed, and VOSviewer software was used to visualise trends. The result showed an increase in publications and citations in the past 20 years indicating the rising interest on heavy metal contamination in the Antarctic region. Based on the analysis of keywords, the publications largely discuss various types of heavy metals found in the Antarctic water and sediment. The analysis on subject areas detects multiple disciplines involved, wherein the environmental science was well-represented. The top countries and authors producing the most publication in this field were from Australia, China, Brazil and Chile. Numerous efforts have been exercised to investigate heavy metal pollution and its mitigation approaches in the region in the past decades. This paper not only is relevant for scholars to understand the development status and trends in this field but also offers clear insights on the future direction of Antarctic heavy metal contamination and remediation research.
  15. Fulltext The Mechanistic Action of Biosynthesised Silver Nanoparticles and Its Application in Aquaculture and Livestock Industries
    De Silva C, Nawawi NM, Abd Karim MM, Abd Gani S, Masarudin MJ, Gunasekaran B, et al.
    Animals (Basel), 2021 Jul 14;11(7).
    PMID: 34359224 DOI: 10.3390/ani11072097
    Nanotechnology is a rapidly developing field due to the emergence of various resistant pathogens and the failure of commercial methods of treatment. AgNPs have emerged as one of the best nanotechnology metal nanoparticles due to their large surface-to-volume ratio and success and efficiency in combating various pathogens over the years, with the biological method of synthesis being the most effective and environmentally friendly method. The primary mode of action of AgNPs against pathogens are via their cytotoxicity, which is influenced by the size and shape of the nanoparticles. The cytotoxicity of the AgNPs gives rise to various theorized mechanisms of action of AgNPs against pathogens such as activation of reactive oxygen species, attachment to cellular membranes, intracellular damage and inducing the viable but non-culturable state (VBNC) of pathogens. This review will be centred on the various theorized mechanisms of actions and its application in the aquaculture, livestock and poultry industries. The application of AgNPs in aquaculture is focused around water treatment, disease control and aquatic nutrition, and in the livestock application it is focused on livestock and poultry.
  16. Fulltext Inertial Sensor-Based Instrumented Cane for Real-Time Walking Cane Kinematics Estimation
    Fernandez IG, Ahmad SA, Wada C
    Sensors (Basel), 2020 Aug 19;20(17).
    PMID: 32825029 DOI: 10.3390/s20174675
    Falls are among the main causes of injuries in elderly individuals. Balance and mobility impairment are major indicators of fall risk in this group. The objective of this research was to develop a fall risk feedback system that operates in real time using an inertial sensor-based instrumented cane. Based on inertial sensor data, the proposed system estimates the kinematics (contact phase and orientation) of the cane. First, the contact phase of the cane was estimated by a convolutional neural network. Next, various algorithms for the cane orientation estimation were compared and validated using an optical motion capture system. The proposed cane contact phase prediction model achieved higher accuracy than the previous models. In the cane orientation estimation, the Madgwick filter yielded the best results overall. Finally, the proposed system was able to estimate both the contact phase and orientation in real time in a single-board computer.
  17. Fulltext Production of Lipopeptide Biosurfactant by a Hydrocarbon-Degrading Antarctic Rhodococcus
    Habib S, Ahmad SA, Wan Johari WL, Abd Shukor MY, Alias SA, Smykla J, et al.
    Int J Mol Sci, 2020 Aug 26;21(17).
    PMID: 32858859 DOI: 10.3390/ijms21176138
    Rhodococci are renowned for their great metabolic repertoire partly because of their numerous putative pathways for large number of specialized metabolites such as biosurfactant. Screening and genome-based assessment for the capacity to produce surface-active molecules was conducted on Rhodococcus sp. ADL36, a diesel-degrading Antarctic bacterium. The strain showed a positive bacterial adhesion to hydrocarbon (BATH) assay, drop collapse test, oil displacement activity, microplate assay, maximal emulsification index at 45% and ability to reduce water surface tension to < 30 mN/m. The evaluation of the cell-free supernatant demonstrated its high stability across the temperature, pH and salinity gradient although no correlation was found between the surface and emulsification activity. Based on the positive relationship between the assessment of macromolecules content and infrared analysis, the extracted biosurfactant synthesized was classified as a lipopeptide. Prediction of the secondary metabolites in the non-ribosomal peptide synthetase (NRPS) clusters suggested the likelihood of the surface-active lipopeptide production in the strain's genomic data. This is the third report of surface-active lipopeptide producers from this phylotype and the first from the polar region. The lipopeptide synthesized by ADL36 has the prospect to be an Antarctic remediation tool while furnishing a distinctive natural product for biotechnological application and research.
  18. Fulltext Evaluation of conventional and response surface level optimisation of n-dodecane (n-C12) mineralisation by psychrotolerant strains isolated from pristine soil at Southern Victoria Island, Antarctica
    Habib S, Ahmad SA, Johari WLW, Shukor MYA, Alias SA, Khalil KA, et al.
    Microb Cell Fact, 2018 Mar 17;17(1):44.
    PMID: 29549881 DOI: 10.1186/s12934-018-0889-8
    BACKGROUND: Biodegradation of hydrocarbons in Antarctic soil has been reported to be achieved through the utilisation of indigenous cold-adapted microorganisms. Although numerous bacteria isolated from hydrocarbon-contaminated sites in Antarctica were able to demonstrate promising outcomes in utilising hydrocarbon components as their energy source, reports on the utilisation of hydrocarbons by strains isolated from pristine Antarctic soil are scarce. In the present work, two psychrotolerant strains isolated from Antarctic pristine soil with the competency to utilise diesel fuel as the sole carbon source were identified and optimised through conventional and response surface method.

    RESULTS: Two potent hydrocarbon-degraders (ADL15 and ADL36) were identified via partial 16S rRNA gene sequence analysis, and revealed to be closely related to the genus Pseudomonas and Rhodococcus sp., respectively. Factors affecting diesel degradation such as temperature, hydrocarbon concentration, pH and salt tolerance were studied. Although strain ADL36 was able to withstand a higher concentration of diesel than strain ADL15, both strains showed similar optimal condition for the cell's growth at pH 7.0 and 1.0% (w/v) NaCl at the conventional 'one-factor-at-a-time' level. Both strains were observed to be psychrotrophs with optimal temperatures of 20 °C. Qualitative and quantitative analysis were performed with a gas chromatograph equipped with a flame ionisation detector to measure the reduction of n-alkane components in diesel. In the pre-screening medium, strain ADL36 showed 83.75% of n-dodecane mineralisation while the reduction of n-dodecane by strain ADL15 was merely at 22.39%. The optimised condition for n-dodecane mineralisation predicted through response surface methodology enhanced the reduction of n-dodecane to 99.89 and 38.32% for strain ADL36 and strain ADL15, respectively.

    CONCLUSIONS: Strain ADL36 proves to be a better candidate for bioaugmentation operations on sites contaminated with aliphatic hydrocarbons especially in the Antarctic and other cold regions. The results obtained throughout strongly supports the use of RSM for medium optimisation.

  19. Fulltext Hexavalent molybdenum reduction to mo-blue by a sodium-dodecyl-sulfate-degrading Klebsiella oxytoca strain DRY14
    Halmi MI, Zuhainis SW, Yusof MT, Shaharuddin NA, Helmi W, Shukor Y, et al.
    Biomed Res Int, 2013;2013:384541.
    PMID: 24383052 DOI: 10.1155/2013/384541
    Bacteria with the ability to tolerate, remove, and/or degrade several xenobiotics simultaneously are urgently needed for remediation of polluted sites. A previously isolated bacterium with sodium dodecyl sulfate- (SDS-) degrading capacity was found to be able to reduce molybdenum to the nontoxic molybdenum blue. The optimal pH, carbon source, molybdate concentration, and temperature supporting molybdate reduction were pH 7.0, glucose at 1.5% (w/v), between 25 and 30 mM, and 25°C, respectively. The optimum phosphate concentration for molybdate reduction was 5 mM. The Mo-blue produced exhibits an absorption spectrum with a maximum peak at 865 nm and a shoulder at 700 nm. None of the respiratory inhibitors tested showed any inhibition to the molybdenum-reducing activity suggesting that the electron transport system of this bacterium is not the site of molybdenum reduction. Chromium, cadmium, silver, copper, mercury, and lead caused approximately 77, 65, 77, 89, 80, and 80% inhibition of the molybdenum-reducing activity, respectively. Ferrous and stannous ions markedly increased the activity of molybdenum-reducing activity in this bacterium. The maximum tolerable concentration of SDS as a cocontaminant was 3 g/L. The characteristics of this bacterium make it a suitable candidate for molybdenum bioremediation of sites cocontaminated with detergent pollutant.
  20. Investigating the performance of an amplitude-independent algorithm for detecting the hand muscle activity of stroke survivors
    Hameed HK, Wan Hasan WZ, Shafie S, Ahmad SA, Jaafar H, Inche Mat LN
    J Med Eng Technol, 2020 Apr;44(3):139-148.
    PMID: 32396756 DOI: 10.1080/03091902.2020.1753838
    To make robotic hand devices controlled by surface electromyography (sEMG) signals feasible and practical tools for assisting patients with hand impairments, the problems that prevent these devices from being widely used have to be overcome. The most significant problem is the involuntary amplitude variation of the sEMG signals due to the movement of electrodes during forearm motion. Moreover, for patients who have had a stroke or another neurological disease, the muscle activity of the impaired hand is weak and has a low signal-to-noise ratio (SNR). Thus, muscle activity detection methods intended for controlling robotic hand devices should not depend mainly on the amplitude characteristics of the sEMG signal in the detection process, and they need to be more reliable for sEMG signals that have a low SNR. Since amplitude-independent muscle activity detection methods meet these requirements, this paper investigates the performance of such a method on people who have had a stroke in terms of the detection of weak muscle activity and resistance to false alarms caused by the involuntary amplitude variation of sEMG signals; these two parameters are very important for achieving the reliable control of robotic hand devices intended for people with disabilities. A comparison between the performance of an amplitude-independent muscle activity detection algorithm and three amplitude-dependent algorithms was conducted by using sEMG signals recorded from six hemiparesis stroke survivors and from six healthy subjects. The results showed that the amplitude-independent algorithm performed better in terms of detecting weak muscle activity and resisting false alarms.
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