Displaying publications 21 - 40 of 66 in total

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  1. Religious coping and psychological well-being among Iranian stroke caregivers
    Gholamzadeh S, Hamid TA, Basri H, Sharif F, Ibrahim R
    Iran J Nurs Midwifery Res, 2014 Sep;19(5):478-84.
    PMID: 25400675
    BACKGROUND: This study aims to explore the relationship between religiosity and psychological well-being of caregivers of stroke survivors in Shiraz, Iran.
    MATERIALS AND METHODS: A purposive sample of 96 family members, which included 34 daughters-in-law and 62 daughters, who were caring for severe impaired stroke survivors were enrolled in the study.
    RESULTS: The results showed a significant correlation between positive religious coping and caregivers' psychological well-being. Positive religious coping accounted for 7.2% of the change in psychological well-being. There was no significant association between demographic factors and caregivers' psychological well-being.
    CONCLUSIONS: Our results indicated that religious and spiritual belief have a role in caregiver adaptations with the situation. Therefore, in future studies, it is suggested to concentrate on the effects of other characteristics than the demographic variables on psychological well-being.
    KEYWORDS:Aging; caregivers; mental health; religious coping; stroke
  2. Feature extraction using Hough transform for solid waste bin level detection and classification
    Hannan MA, Zaila WA, Arebey M, Begum RA, Basri H
    Environ Monit Assess, 2014 Sep;186(9):5381-91.
    PMID: 24829160 DOI: 10.1007/s10661-014-3786-6
    This paper deals with the solid waste image detection and classification to detect and classify the solid waste bin level. To do so, Hough transform techniques is used for feature extraction to identify the line detection based on image's gradient field. The feedforward neural network (FFNN) model is used to classify the level content of solid waste based on learning concept. Numbers of training have been performed using FFNN to learn and match the targets of the testing images to compute the sum squared error with the performance goal met. The images for each class are used as input samples for classification. Result from the neural network and the rules decision are used to build the receiver operating characteristic (ROC) graph. Decision graph shows the performance of the system waste system based on area under curve (AUC), WS-class reached 0.9875 for excellent result and WS-grade reached 0.8293 for good result. The system has been successfully designated with the motivation of solid waste bin monitoring system that can applied to a wide variety of local municipal authorities system.
  3. Managing post stroke hyperglycaemia: moderate glycaemic control is better? An update
    Wan Sulaiman WA, Hashim HZ, Che Abdullah ST, Hoo FK, Basri H
    EXCLI J, 2014;13:825-33.
    PMID: 26417305
    Post stroke hyperglycaemia (PSH) is prevalent in acute ischaemic stroke (AIS) patients and it has been associated with a dismal outcome of death and disability. Insulin has been proven to attenuate glucose effectively in stroke patients, thus many trials over the years had studied the efficacy of intensive treatment aiming at normalization of blood sugar level in order to improve the bleak outcomes of PSH. However, tight glycaemic control failed to be translated into clinical benefits and the outcomes are no different from the conventional approach, despite the costly healthcare expenditure invested. On the contrary, it brings more significant harm than the intended benefit, as 1 in every 9 treated patients had symptomatic hypoglycaemia. Thus, the benefits of tight glucose control, if any, are overshadowed by this potential risk of hypoglycaemia causing permanent neurological injury. Therefore, international practice guidelines recommend for less aggressive treatment to maintain blood glucose level within an appropriate range in AIS patients. However, there are limited details for stroke-specific glycaemic management and this made management of PSH particularly difficult. This review is to discuss and provide suggestions concerning glycaemic control in acute ischaemic stroke; the direction of its future prospective clinical trials and the treatment strategy required based on recent literature.
  4. A review on technologies and their usage in solid waste monitoring and management systems: Issues and challenges
    Hannan MA, Abdulla Al Mamun M, Hussain A, Basri H, Begum RA
    Waste Manag, 2015 Sep;43:509-23.
    PMID: 26072186 DOI: 10.1016/j.wasman.2015.05.033
    In the backdrop of prompt advancement, information and communication technology (ICT) has become an inevitable part to plan and design of modern solid waste management (SWM) systems. This study presents a critical review of the existing ICTs and their usage in SWM systems to unfold the issues and challenges towards using integrated technologies based system. To plan, monitor, collect and manage solid waste, the ICTs are divided into four categories such as spatial technologies, identification technologies, data acquisition technologies and data communication technologies. The ICT based SWM systems classified in this paper are based on the first three technologies while the forth one is employed by almost every systems. This review may guide the reader about the basics of available ICTs and their application in SWM to facilitate the search for planning and design of a sustainable new system.
  5. Solid waste forecasting using modified ANFIS modeling
    Younes MK, Nopiah ZM, Basri NE, Basri H, Abushammala MF, K N A M
    J Air Waste Manag Assoc, 2015 Oct;65(10):1229-38.
    PMID: 26223583 DOI: 10.1080/10962247.2015.1075919
    Solid waste prediction is crucial for sustainable solid waste management. Usually, accurate waste generation record is challenge in developing countries which complicates the modelling process. Solid waste generation is related to demographic, economic, and social factors. However, these factors are highly varied due to population and economy growths. The objective of this research is to determine the most influencing demographic and economic factors that affect solid waste generation using systematic approach, and then develop a model to forecast solid waste generation using a modified Adaptive Neural Inference System (MANFIS). The model evaluation was performed using Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and the coefficient of determination (R²). The results show that the best input variables are people age groups 0-14, 15-64, and people above 65 years, and the best model structure is 3 triangular fuzzy membership functions and 27 fuzzy rules. The model has been validated using testing data and the resulted training RMSE, MAE and R² were 0.2678, 0.045 and 0.99, respectively, while for testing phase RMSE =3.986, MAE = 0.673 and R² = 0.98.
  6. Fulltext Guillain-Barré syndrome complicating dengue fever: Two case reports
    Boo YL, Aris MAM, Chin PW, Sulaiman WAW, Basri H, Hoo FK
    Ci Ji Yi Xue Za Zhi, 2015 11 17;28(4):157-159.
    PMID: 28757747 DOI: 10.1016/j.tcmj.2015.09.007
    Guillain-Barré syndrome is a rare neurological manifestation associated with dengue infection. More common antecedent infections include Campylobacter jejuni and Cytomegalovirus infection. Here, we report two cases of Guillain-Barré syndrome complicating dengue infection.
  7. Prediction of municipal solid waste generation using nonlinear autoregressive network
    Younes MK, Nopiah ZM, Basri NE, Basri H, Abushammala MF, Maulud KN
    Environ Monit Assess, 2015 Dec;187(12):753.
    PMID: 26573690 DOI: 10.1007/s10661-015-4977-5
    Most of the developing countries have solid waste management problems. Solid waste strategic planning requires accurate prediction of the quality and quantity of the generated waste. In developing countries, such as Malaysia, the solid waste generation rate is increasing rapidly, due to population growth and new consumption trends that characterize society. This paper proposes an artificial neural network (ANN) approach using feedforward nonlinear autoregressive network with exogenous inputs (NARX) to predict annual solid waste generation in relation to demographic and economic variables like population number, gross domestic product, electricity demand per capita and employment and unemployment numbers. In addition, variable selection procedures are also developed to select a significant explanatory variable. The model evaluation was performed using coefficient of determination (R(2)) and mean square error (MSE). The optimum model that produced the lowest testing MSE (2.46) and the highest R(2) (0.97) had three inputs (gross domestic product, population and employment), eight neurons and one lag in the hidden layer, and used Fletcher-Powell's conjugate gradient as the training algorithm.
  8. Content-based image retrieval system for solid waste bin level detection and performance evaluation
    Hannan MA, Arebey M, Begum RA, Basri H, Al Mamun MA
    Waste Manag, 2016 Apr;50:10-9.
    PMID: 26868844 DOI: 10.1016/j.wasman.2016.01.046
    This paper presents a CBIR system to investigate the use of image retrieval with an extracted texture from the image of a bin to detect the bin level. Various similarity distances like Euclidean, Bhattacharyya, Chi-squared, Cosine, and EMD are used with the CBIR system for calculating and comparing the distance between a query image and the images in a database to obtain the highest performance. In this study, the performance metrics is based on two quantitative evaluation criteria. The first one is the average retrieval rate based on the precision-recall graph and the second is the use of F1 measure which is the weighted harmonic mean of precision and recall. In case of feature extraction, texture is used as an image feature for bin level detection system. Various experiments are conducted with different features extraction techniques like Gabor wavelet filter, gray level co-occurrence matrix (GLCM), and gray level aura matrix (GLAM) to identify the level of the bin and its surrounding area. Intensive tests are conducted among 250bin images to assess the accuracy of the proposed feature extraction techniques. The average retrieval rate is used to evaluate the performance of the retrieval system. The result shows that, the EMD distance achieved high accuracy and provides better performance than the other distances.
  9. Landfill area estimation based on integrated waste disposal options and solid waste forecasting using modified ANFIS model
    Younes MK, Nopiah ZM, Basri NE, Basri H, Abushammala MF, Younes MY
    Waste Manag, 2016 Sep;55:3-11.
    PMID: 26522806 DOI: 10.1016/j.wasman.2015.10.020
    Solid waste prediction is crucial for sustainable solid waste management. The collection of accurate waste data records is challenging in developing countries. Solid waste generation is usually correlated with economic, demographic and social factors. However, these factors are not constant due to population and economic growth. The objective of this research is to minimize the land requirements for solid waste disposal for implementation of the Malaysian vision of waste disposal options. This goal has been previously achieved by integrating the solid waste forecasting model, waste composition and the Malaysian vision. The modified adaptive neural fuzzy inference system (MANFIS) was employed to develop a solid waste prediction model and search for the optimum input factors. The performance of the model was evaluated using the root mean square error (RMSE) and the coefficient of determination (R(2)). The model validation results are as follows: RMSE for training=0.2678, RMSE for testing=3.9860 and R(2)=0.99. Implementation of the Malaysian vision for waste disposal options can minimize the land requirements for waste disposal by up to 43%.
  10. Fulltext Modulation of Hydrogen Peroxide-Induced Oxidative Stress in Human Neuronal Cells by Thymoquinone-Rich Fraction and Thymoquinone via Transcriptomic Regulation of Antioxidant and Apoptotic Signaling Genes
    Ismail N, Ismail M, Azmi NH, Abu Bakar MF, Basri H, Abdullah MA
    Oxid Med Cell Longev, 2016;2016:2528935.
    PMID: 26823946 DOI: 10.1155/2016/2528935
    Nigella sativa Linn. (N. sativa) and its bioactive constituent Thymoquinone (TQ) have demonstrated numerous pharmacological attributes. In the present study, the neuroprotective properties of Thymoquinone-rich fraction (TQRF) and TQ against hydrogen peroxide- (H2O2-) induced neurotoxicity in differentiated human SH-SY5Y cells were investigated. TQRF was extracted using supercritical fluid extraction while TQ was acquired commercially, and their effects on H2O2 were evaluated using cell viability assay, reactive oxygen species (ROS) assay, morphological observation, and multiplex gene expression. Both TQRF and TQ protected the cells against H2O2 by preserving the mitochondrial metabolic enzymes, reducing intracellular ROS levels, preserving morphological architecture, and modulating the expression of genes related to antioxidants (SOD1, SOD2, and catalase) and signaling genes (p53, AKT1, ERK1/2, p38 MAPK, JNK, and NF-κβ). In conclusion, the enhanced efficacy of TQRF over TQ was likely due to the synergism of multiple constituents in TQRF. The efficacy of TQRF was better than that of TQ alone when equal concentrations of TQ in TQRF were compared. In addition, TQRF also showed comparable effects to TQ when the same concentrations were tested. These findings provide further support for the use of TQRF as an alternative to combat oxidative stress insults in neurodegenerative diseases.
  11. Backtracking search algorithm in CVRP models for efficient solid waste collection and route optimization
    Akhtar M, Hannan MA, Begum RA, Basri H, Scavino E
    Waste Manag, 2017 Mar;61:117-128.
    PMID: 28153405 DOI: 10.1016/j.wasman.2017.01.022
    Waste collection is an important part of waste management that involves different issues, including environmental, economic, and social, among others. Waste collection optimization can reduce the waste collection budget and environmental emissions by reducing the collection route distance. This paper presents a modified Backtracking Search Algorithm (BSA) in capacitated vehicle routing problem (CVRP) models with the smart bin concept to find the best optimized waste collection route solutions. The objective function minimizes the sum of the waste collection route distances. The study introduces the concept of the threshold waste level (TWL) of waste bins to reduce the number of bins to be emptied by finding an optimal range, thus minimizing the distance. A scheduling model is also introduced to compare the feasibility of the proposed model with that of the conventional collection system in terms of travel distance, collected waste, fuel consumption, fuel cost, efficiency and CO2 emission. The optimal TWL was found to be between 70% and 75% of the fill level of waste collection nodes and had the maximum tightness value for different problem cases. The obtained results for four days show a 36.80% distance reduction for 91.40% of the total waste collection, which eventually increases the average waste collection efficiency by 36.78% and reduces the fuel consumption, fuel cost and CO2 emission by 50%, 47.77% and 44.68%, respectively. Thus, the proposed optimization model can be considered a viable tool for optimizing waste collection routes to reduce economic costs and environmental impacts.
  12. Acute disseminated encephalomyelitis in dengue viral infection
    Wan Sulaiman WA, Inche Mat LN, Hashim HZ, Hoo FK, Ching SM, Vasudevan R, et al.
    J Clin Neurosci, 2017 Sep;43:25-31.
    PMID: 28625589 DOI: 10.1016/j.jocn.2017.05.033
    Dengue is the most common arboviral disease affecting many countries worldwide. An RNA virus from the flaviviridae family, dengue has four antigenically distinct serotypes (DEN-1-DEN-4). Neurological involvement in dengue can be classified into dengue encephalopathy immune-mediated syndromes, encephalitis, neuromuscular or dengue muscle dysfunction and neuro-ophthalmic involvement. Acute disseminated encephalomyelitis (ADEM) is an immune mediated acute demyelinating disorder of the central nervous system following recent infection or vaccination. This monophasic illness is characterised by multifocal white matter involvement. Many dengue studies and case reports have linked ADEM with dengue virus infection but the association is still not clear. Therefore, this article is to review and discuss concerning ADEM in dengue as an immune-medicated neurological complication; and the management strategy required based on recent literature.
  13. Beneficial effects of TQRF and TQ nano- and conventional emulsions on memory deficit, lipid peroxidation, total antioxidant status, antioxidants genes expression and soluble Aβ levels in high fat-cholesterol diet-induced rats
    Ismail N, Ismail M, Azmi NH, Bakar MFA, Yida Z, Stanslas J, et al.
    Chem Biol Interact, 2017 Sep 25;275:61-73.
    PMID: 28734741 DOI: 10.1016/j.cbi.2017.07.014
    The study determined the effect of thymoquinone rich fraction (TQRF) and thymoquinone (TQ) in the forms of nano- and conventional emulsions on learning and memory, lipid peroxidation, total antioxidant status, antioxidants genes expression and soluble β-amyloid (Aβ) levels in rats fed with a high fat-cholesterol diet (HFCD). The TQRF was extracted from Nigella sativa seeds using a supercritical fluid extraction system and prepared into nanoemulsion, which later named as TQRF nanoemulsion (TQRFNE). Meanwhile, TQ was acquired commercially and prepared into thymoquinone nanoemulsion (TQNE). The TQRF and TQ conventional emulsions (CE), named as TQRFCE and TQCE, respectively were studied for comparison. Statin (simvastatin) and non-statin (probucol) cholesterol-lowering agents, and a mild-to-severe Alzheimer's disease drug (donepezil) were served as control drugs. The Sprague Dawley rats were fed with HFCD for 6 months, and treated with the intervention groups via oral gavage daily for the last 3 months. As a result, HFCD-fed rats exhibited hypercholesterolaemia, accompanied by memory deficit, increment of lipid peroxidation and soluble Aβ levels, decrement of total antioxidant status and down-regulation of antioxidants genes expression levels. TQRFNE demonstrated comparable effects to the other intervention groups and control drugs in serum biomarkers as well as in the learning and memory test. Somehow, TQRFNE was more prominent than those intervention groups and control drugs in brain biomarkers concomitant to gene and protein expression levels. Supplementation of TQRFNE into an HFCD thus could ameliorate memory deficit, lipid peroxidation and soluble Aβ levels as well as improving the total antioxidant status and antioxidants genes expression levels.
  14. Thymoquinone-rich fraction nanoemulsion (TQRFNE) decreases Aβ40 and Aβ42 levels by modulating APP processing, up-regulating IDE and LRP1, and down-regulating BACE1 and RAGE in response to high fat/cholesterol diet-induced rats
    Ismail N, Ismail M, Azmi NH, Bakar MFA, Yida Z, Abdullah MA, et al.
    Biomed Pharmacother, 2017 Nov;95:780-788.
    PMID: 28892789 DOI: 10.1016/j.biopha.2017.08.074
    Though the causes of Alzheimer's disease (AD) are yet to be understood, much evidence has suggested that excessive amyloid-β (Aβ) accumulation due to abnormal amyloid-β precursor protein (APP) processing and Aβ metabolism are crucial processes towards AD pathogenesis. Hence, approaches aiming at APP processing and Aβ metabolism are currently being actively pursued for the management of AD. Studies suggest that high cholesterol and a high fat diet have harmful effects on cognitive function and may instigate the commencement of AD pathogenesis. Despite the neuropharmacological attributes of black cumin seed (Nigella sativa) extracts and its main active compound, thymoquinone (TQ), limited records are available in relation to AD research. Nanoemulsion (NE) is exploited as drug delivery systems due to their capacity of solubilising non-polar active compounds and is widely examined for brain targeting. Herewith, the effects of thymoquinone-rich fraction nanoemulsion (TQRFNE), thymoquinone nanoemulsion (TQNE) and their counterparts' conventional emulsion in response to high fat/cholesterol diet (HFCD)-induced rats were investigated. Particularly, the Aβ generation; APP processing, β-secretase 1 (BACE1), γ-secretases of presenilin 1 (PSEN1) and presenilin 2 (PSEN2), Aβ degradation; insulin degrading enzyme (IDE), Aβ transportation; low density lipoprotein receptor-related protein 1 (LRP1) and receptor for advanced glycation end products (RAGE) were measured in brain tissues. TQRFNE reduced the brain Aβ fragment length 1-40 and 1-42 (Aβ40 and Aβ42) levels, which would attenuate the AD pathogenesis. This reduction could be due to the modulation of β- and γ-secretase enzyme activity, and the Aβ degradation and transportation in/out of the brain. The findings show the mechanistic actions of TQRFNE in response to high fat and high cholesterol diet associated to Aβ generation, degradation and transportation in the rat's brain tissue.
  15. Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm
    Hannan MA, Akhtar M, Begum RA, Basri H, Hussain A, Scavino E
    Waste Manag, 2018 Jan;71:31-41.
    PMID: 29079284 DOI: 10.1016/j.wasman.2017.10.019
    Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70-75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts.
  16. Fulltext Challenges faced and lessons learned A multi-component prospective memory training program for Malaysian older adults
    Farzin A, Ibrahim R, Madon Z, Basri H
    Dement Neuropsychol, 2018 7 11;12(2):189-195.
    PMID: 29988335 DOI: 10.1590/1980-57642018dn12-020012
    The surrounding circumstances and environments of Malaysian older adults could make conducting interventions (mainly in terms of clinical or randomized controlled trials) a challenge. Working with older adults and facing cultural issues could be challenging.

    Objective: This paper illustrates a significant perspective of some of the challenges faced while conducting a randomized controlled trial exploring the impact of a multi-component intervention that included strategy- and process-based prospective memory (PM) training among Malaysian older adults.

    Methods: The current study was a randomized controlled trial (RCT) and therefore the challenges were presented in accordance with the CONSORT statement style.

    Results: A discussion on how these issues were addressed is provided.

    Conclusion: Some suggestions were presented to help researchers plan and create interventions for similar studies and to support a practical method of addressing all related challenges.

  17. The Efficiency of a Multicomponent Training for Prospective Memory Among Healthy Older Adults: A Single-Blind, Randomized Controlled Within-Participants Cross-Over Trial
    Farzin A, Ibrahim R, Madon Z, Basri H
    Am J Phys Med Rehabil, 2018 09;97(9):628-635.
    PMID: 29595585 DOI: 10.1097/PHM.0000000000000931
    OBJECTIVE: The main objective of the present trial was to evaluate the efficiency of a preventative multicomponent prospective memory training among healthy older adults.

    DESIGN: This study was a two-arm within-participants trial with 4- and 12-wk follow-ups. Allocation ratio was 1:1, and pretraining and posttraining measurements were included. A total number of 25 healthy older adults were enrolled (mean = 63.32, SD = 4.44). Participants were randomly allocated into two conditions: (a) prospective memory training: participants underwent a multicomponent prospective memory training, and (b) control: participants were not contacted during the training phase. After the training phase was finished, participants crossed over to undergo the condition they did not experience before. The differences between pretraining and posttraining measures of prospective memory, activities of daily living, negative mood (depression), and anxiety were assessed. All changes in the measurements were analyzed using general linear method. This trial is registered at https://www.isrctn.com (#ISRCTN57600070).

    RESULTS: Multicomponent prospective memory training program was significantly effective on both subjective and objective prospective memory performances among healthy older adults. Moreover, the training had significant positive effects on activities of daily living (independence) among participants. In addition, negative mood and anxiety levels were reduced after the training was finished.

    CONCLUSIONS: This multicomponent prospective memory training improved prospective memory performance and activities of daily living and reduce negative mood (depression) and anxiety levels among healthy older adults.

  18. Fulltext Factors influencing consumers’ preferences towards meat and meat products with traceability systems in Malaysia
    Basri, H. N., Kamarulzaman, N. H., Shamsudin, M. N., Nolila Mohd Nawi
    International Food Research Journal, 2018;25(102):157-164.
    MyJurnal
    Majority consumers around the world have become increasingly concern and aware about their health and food safety. Recent food crisis and foodborne illness incidents showed the needs to assure the authenticity and traceability of foods in the market especially meat and meat products. These scandals have led to negative effect and perception to consumers, food companies and both supply and demand chain. Hence, the food industry needs an excellent and reliable traceability system to ensure that consumers are persistently well protected from unconscious consumption of unsafe foods. Therefore, traceability systems can support the claims by making it verifiable. However, the awareness among Malaysian consumers is still lacking due to the inadequate exposure towards concept and the importance of traceability systems particularly in meat and meat products. The aim of this study is to determine factors influencing consumers’ preferences towards traceability systems of meat and meat products in Malaysia. Primary data were collected using structured questionnaire via face to face interview with 503 respondents in Klang Valley, Malaysia. Data collected were analyzed using descriptive and factor analysis. The findings of descriptive analysis showed that most of the consumers preferred using traceability systems and aware of its importance when buying meat and meat products. Meanwhile, the factor analysis results discovered six factors that influenced consumers’ preferences towards meat and meat products with traceability systems namely Halal certificate, transparency, quality, confidence, food safety and knowledge. Therefore, implementation of traceability systems could raise standards of food safety throughout the meat production supply chain. Furthermore, the society will become more confident and they can benefit from the quality of purchase and consumption. The findings from this study are also able to contribute to the body of knowledge to the producers or marketers towards food safety issues and foodborne illness that recently happened in Malaysia.
  19. Fulltext Arsenic Resistance and Biosorption by Isolated Rhizobacteria from the Roots of Ludwigia octovalvis
    Titah HS, Abdullah SRS, Idris M, Anuar N, Basri H, Mukhlisin M, et al.
    Int J Microbiol, 2018;2018:3101498.
    PMID: 30723505 DOI: 10.1155/2018/3101498
    Certain rhizobacteria can be applied to remove arsenic in the environment through bioremediation or phytoremediation. This study determines the minimum inhibitory concentration (MIC) of arsenic on identified rhizobacteria that were isolated from the roots of Ludwigia octovalvis (Jacq.) Raven. The arsenic biosorption capability of the was also analyzed. Among the 10 isolated rhizobacteria, five were Gram-positive (Arthrobacter globiformis, Bacillus megaterium, Bacillus cereus, Bacillus pumilus, and Staphylococcus lentus), and five were Gram-negative (Enterobacter asburiae, Sphingomonas paucimobilis, Pantoea spp., Rhizobium rhizogenes, and Rhizobium radiobacter). R. radiobacter showed the highest MIC of >1,500 mg/L of arsenic. All the rhizobacteria were capable of absorbing arsenic, and S. paucimobilis showed the highest arsenic biosorption capability (146.4 ± 23.4 mg/g dry cell weight). Kinetic rate analysis showed that B. cereus followed the pore diffusion model (R2 = 0.86), E. asburiae followed the pseudo-first-order kinetic model (R2 = 0.99), and R. rhizogenes followed the pseudo-second-order kinetic model (R2 = 0.93). The identified rhizobacteria differ in their mechanism of arsenic biosorption, arsenic biosorption capability, and kinetic models in arsenic biosorption.
  20. Fulltext Effect of Edible Bird's Nest Extract on Lipopolysaccharide-Induced Impairment of Learning and Memory in Wistar Rats
    Careena S, Sani D, Tan SN, Lim CW, Hassan S, Norhafizah M, et al.
    Evid Based Complement Alternat Med, 2018;2018:9318789.
    PMID: 30186358 DOI: 10.1155/2018/9318789
    Cognitive disability is a common feature associated with a variety of neurological conditions including Alzheimer's Disease (AD), Parkinson's Disease (PD), brain injury, and stroke. Emerging evidence has demonstrated that neuroinflammation plays an important role in the development of cognitive impairment. Current available therapies are relatively ineffective in treating or preventing cognitive disabilities, thus representing an important, unfulfilled medical need. Hence, developing potential treatment is one of the major areas of research interest. Edible bird's nests (EBN) are nests formed by swiftlet's saliva containing sialic acid, which is believed to improve brain function. This present study was embarked upon to evaluate the learning and memory enhancing potential effect of EBN by using Morris water maze test in a Wistar rat model of LPS-induced neuroinflammation. LPS elicited cognitive impairment in the rats by significantly increasing the escape latency while decreasing the number of entries in the probe trial, which are coupled with increased production of proinflammatory cytokines (TNF-α, IL-1β, and IL-6) and oxidative markers (ROS and TBARS) in the hippocampus. Treatment with EBN (125 mg/kg, 250 mg/kg, and 500 mg/kg; p.o.) effectively reversed the effect of LPS on escape latency and probe trial and, in addition, inhibited the LPS-induced upregulation of proinflammatory cytokines and oxidative markers. These findings are suggestive that there is existence of neuroprotective effect contained inside the edible bird's nest.
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