Displaying publications 621 - 640 of 6712 in total

Abstract:
Sort:
  1. Fulltext SuCComBase: a manually curated repository of plant sulfur-containing compounds
    Harun S, Abdullah-Zawawi MR, A-Rahman MRA, Muhammad NAN, Mohamed-Hussein ZA
    Database (Oxford), 2019 01 01;2019.
    PMID: 30793170 DOI: 10.1093/database/baz021
    Plants produce a wide range of secondary metabolites that play important roles in plant defense and immunity, their interaction with the environment and symbiotic associations. Sulfur-containing compounds (SCCs) are a group of important secondary metabolites produced in members of the Brassicales order. SCCs constitute various groups of phytochemicals, but not much is known about them. Findings from previous studies on SCCs were scattered in published literatures, hence SuCComBase was developed to store all molecular information related to the biosynthesis of SCCs. Information that includes genes, proteins and compounds that are involved in the SCC biosynthetic pathway was manually identified from databases and published scientific literatures. Sets of co-expression data was analyzed to search for other possible (previously unknown) genes that might be involved in the biosynthesis of SCC. These genes were named as potential SCC-related encoding genes. A total of 147 known and 92 putative Arabidopsis thaliana SCC-related genes from literatures were used to identify other potential SCC-related encoding genes. We identified 778 potential SCC-related encoding genes, 4026 homologs to the SCC-related encoding genes and 116 SCCs as shown on SuCComBase homepage. Data entries are searchable from the Main page, Search, Browse and Datasets tabs. Users can easily download all data stored in SuCComBase. All publications related to SCCs are also indexed in SuCComBase, which is currently the first and only database dedicated to plant SCCs. SuCComBase aims to become a manually curated and au fait knowledge-based repository for plant SCCs.
  2. Fulltext Insight into plant cell wall degradation and pathogenesis of Ganoderma boninense via comparative genome analysis
    Ramzi AB, Che Me ML, Ruslan US, Baharum SN, Nor Muhammad NA
    PeerJ, 2019;7:e8065.
    PMID: 31879570 DOI: 10.7717/peerj.8065
    Background: G. boninense is a hemibiotrophic fungus that infects oil palms (Elaeis guineensis Jacq.) causing basal stem rot (BSR) disease and consequent massive economic losses to the oil palm industry. The pathogenicity of this white-rot fungus has been associated with cell wall degrading enzymes (CWDEs) released during saprophytic and necrotrophic stage of infection of the oil palm host. However, there is a lack of information available on the essentiality of CWDEs in wood-decaying process and pathogenesis of this oil palm pathogen especially at molecular and genome levels.

    Methods: In this study, comparative genome analysis was carried out using the G. boninense NJ3 genome to identify and characterize carbohydrate-active enzyme (CAZymes) including CWDE in the fungal genome. Augustus pipeline was employed for gene identification in G. boninense NJ3 and the produced protein sequences were analyzed via dbCAN pipeline and PhiBase 4.5 database annotation for CAZymes and plant-host interaction (PHI) gene analysis, respectively. Comparison of CAZymes from G. boninense NJ3 was made against G. lucidum, a well-studied model Ganoderma sp. and five selected pathogenic fungi for CAZymes characterization. Functional annotation of PHI genes was carried out using Web Gene Ontology Annotation Plot (WEGO) and was used for selecting candidate PHI genes related to cell wall degradation of G. boninense NJ3.

    Results: G. boninense was enriched with CAZymes and CWDEs in a similar fashion to G. lucidum that corroborate with the lignocellulolytic abilities of both closely-related fungal strains. The role of polysaccharide and cell wall degrading enzymes in the hemibiotrophic mode of infection of G. boninense was investigated by analyzing the fungal CAZymes with necrotrophic Armillaria solidipes, A. mellea, biotrophic Ustilago maydis, Melampsora larici-populina and hemibiotrophic Moniliophthora perniciosa. Profiles of the selected pathogenic fungi demonstrated that necrotizing pathogens including G. boninense NJ3 exhibited an extensive set of CAZymes as compared to the more CAZymes-limited biotrophic pathogens. Following PHI analysis, several candidate genes including polygalacturonase, endo β-1,3-xylanase, β-glucanase and laccase were identified as potential CWDEs that contribute to the plant host interaction and pathogenesis.

    Discussion: This study employed bioinformatics tools for providing a greater understanding of the biological mechanisms underlying the production of CAZymes in G. boninense NJ3. Identification and profiling of the fungal polysaccharide- and lignocellulosic-degrading enzymes would further facilitate in elucidating the infection mechanisms through the production of CWDEs by G. boninense. Identification of CAZymes and CWDE-related PHI genes in G. boninense would serve as the basis for functional studies of genes associated with the fungal virulence and pathogenicity using systems biology and genetic engineering approaches.

  3. Fulltext Irritable Bowel Syndrome, Depression, and Neurodegeneration: A Bidirectional Communication from Gut to Brain
    Aziz MNM, Kumar J, Muhammad Nawawi KN, Raja Ali RA, Mokhtar NM
    Nutrients, 2021 Aug 31;13(9).
    PMID: 34578939 DOI: 10.3390/nu13093061
    Patients with irritable bowel syndrome (IBS) are increasingly presenting with a wide range of neuropsychiatric symptoms, such as deterioration in gastroenteric physiology, including visceral hypersensitivity, altered intestinal membrane permeability, and gastrointestinal motor dysfunction. Functional imaging of IBS patients has revealed several abnormalities in various brain regions, such as significant activation of amygdala, thinning of insular and anterior cingulate cortex, and increase in hypothalamic gray matter, which results in poor psychiatric and cognitive outcomes. Interrelations between the enteric and central events in IBS-related gastrointestinal, neurological, and psychiatric pathologies have compelled researchers to study the gut-brain axis-a bidirectional communication that maintains the homeostasis of the gastrointestinal and central nervous system with gut microbiota as the protagonist. Thus, it can be disrupted by any alteration owing to the gut dysbiosis or loss of diversity in microbial composition. Available evidence indicates that the use of probiotics as a part of a balanced diet is effective in the management of IBS and IBS-associated neurodegenerative and psychiatric comorbidities. In this review, we delineate the pathogenesis and complications of IBS from gastrointestinal and neuropsychiatric standpoints while also discussing the neurodegenerative events in enteric and central nervous systems of IBS patients and the therapeutic potential of gut microbiota-based therapy established on clinical and preclinical data.
  4. Micro and nanorobot-based drug delivery: an overview
    Suhail M, Khan A, Rahim MA, Naeem A, Fahad M, Badshah SF, et al.
    J Drug Target, 2021 Nov 09.
    PMID: 34706620 DOI: 10.1080/1061186X.2021.1999962
    Progress in the drug delivery system in the last few decades has led to many advancements for efficient drug delivery. Both micro and nanorobots, are regarded as superior drug delivery systems to deliver drugs efficiently by altering other forms of energy into propulsion and movements. Furthermore, it can be advantageous as it is directed to targeted sites beneath physiological environments and conditions. They have been validated to possess the capability to encapsulate, transport, and supply therapeutic contents directly to the disease sites, thus enhancing the therapeutic efficiency and decreasing systemic side effects of the toxic drugs. This review discusses about the microand nanorobots for the diagnostics and management of diseases, types of micro, and nanorobots, role of robots in drug delivery, and its biomedical applications.
  5. Optimization of Protocol for Isolation of Chondrocytes from Human Articular Cartilage
    Muhammad SA, Nordin N, Hussin P, Mehat MZ, Tan SW, Fakurazi S
    Cartilage, 2021 12;13(2_suppl):872S-884S.
    PMID: 31540551 DOI: 10.1177/1947603519876333
    OBJECTIVE: Cartilage tissue engineering has evolved as one of the therapeutic strategies for cartilage defect, which relies on a large number of viable chondrocytes. Because of limited availability of cartilage and low chondrocytes yield from cartilage, the need for an improve isolation protocol for maximum yield of viable cells is a key to achieving successful clinical constructs. This study optimizes and compares different protocols for isolation of chondrocytes from cartilage.

    DESIGN: We employed enzymatic digestion of cartilage using collagenase II and trypsin. The chondrocytes yield, growth kinetics, aggrecan, and collagen type 2 (COL2) expression were evaluated. Collagen type 1 (COL1) mRNA expression was assessed to monitor the possibility of chondrocytes dedifferentiation.

    RESULTS: Chondrocyte yield per gram of cartilage was significantly higher (P < 0.05) using collagenase II in Hank's balanced salt solution (HBSS) compared with 0.25% trypsin. The number of chondrocyte yield per gram was higher in cartilage digested with collagenase in HBSS compared with Dulbecco's modified Eagle medium/F12; however, the difference was not statistically significant. Chondrocytes seeded at lower densities had shorter population doubling time compared to those seeded at higher density. Protein and gene expression of chondrocyte phenotype indicates the expression of aggrecan and COL2. The expression of COL1 was significantly increased (P < 0.05) in passage 3 compared with primary chondrocytes. The mRNA expression of chondrocyte phenotype was similar in primary and passaged one cells.

    CONCLUSIONS: Collagenase in HBSS yield the highest number of viable chondrocytes and the isolated cells expressed chondrocyte phenotype. This protocol can be employed to generate large number of viable chondrocytes, particularly with limited cartilage biopsies.

  6. Fulltext A Scoping Review of the Factor Associated with Older Adults' Mobility Barriers
    Che Had NH, Alavi K, Md Akhir N, Muhammad Nur IR, Shuhaimi MSZ, Foong HF
    Int J Environ Res Public Health, 2023 Feb 27;20(5).
    PMID: 36901256 DOI: 10.3390/ijerph20054243
    The phenomenon of ageing may contribute to the rise of the dependent population. Due to the obstacles and difficulties they confront, the elderly's mobility decreases significantly. The aim of this article is to identify factors associated with mobility barriers in older adults. The method employed is an examination of articles published between 2011 and 2022 to identify common themes in previous studies. Four search engines were being used, and 32 articles have been included. This study demonstrated that health is a major factor associated with decreased mobility. This review identified four types of barriers which are health, built environment, socio-economic background and social relation change. This review could help policy makers and gerontologist in identifying solutions to resolve the mobility issues in older people.
  7. Application of CHIRPS dataset in the selection of rain-based indices for drought assessments in Johor River Basin, Malaysia
    Sa'adi Z, Yusop Z, Alias NE, Shiru MS, Muhammad MKI, Ramli MWA
    Sci Total Environ, 2023 Sep 20;892:164471.
    PMID: 37257620 DOI: 10.1016/j.scitotenv.2023.164471
    This paper aims to select the most appropriate rain-based meteorological drought index for detecting drought characteristics and identifying tropical drought events in the Johor River Basin (JRB). Based on a multi-step approach, the study evaluated seven drought indices, including the Rainfall Anomaly Index (RAI), Standardized Precipitation Index (SPI), China-Z Index (CZI), Modified China-Z Index (MCZI), Percent of Normal (PN), Deciles Index (DI), and Z-Score Index (ZSI), based on the CHIRPS rainfall gridded-based datasets from 1981 to 2020. Results showed that CZI, MCZI, SPI, and ZSI outperformed the other indices based on their correlation and linearity (R2 = 0.96-0.99) along with their ranking based on the Compromise Programming Index (CPI). The historical drought evaluation revealed that MCZI, SPI, and ZSI performed similarly in detecting drought events, but SPI was more effective in detecting spatial coverage and the occurrence of 'very dry' and 'extremely dry' drought events. Based on SPI, the study found that the downstream area, north-easternmost area, and eastern boundary of the basin were more prone to higher frequency and longer duration droughts. Furthermore, the study found that prolonged droughts are characterized by episodic drought events, which occur with one to three months of 'relief period' before another drought event occurs. The study revealed that most drought events that coincide with El Niño, positive Indian Ocean Dipole (IOD), and negative Madden-Julian Oscillation (MJO) events, or a combination of these events, may worsen drought conditions. The application of CHIRPS datasets enables better spatiotemporal mapping and prediction of drought for JRB, and the output is pertinent for improving water management strategies and adaptation measures. Understanding spatiotemporal drought conditions is crucial to ensuring sustainable development and policies through better regulation of human activities. The framework of this research can be applied to other river basins in Malaysia and other parts of Southeast Asia.
  8. Fulltext Evaluation of 2 Artificial Intelligence Software for Chest X-Ray Screening and Pulmonary Tuberculosis Diagnosis: Protocol for a Retrospective Case-Control Study
    Mohd Hisham MF, Lodz NA, Muhammad EN, Asari FN, Mahmood MI, Abu Bakar Z
    JMIR Res Protoc, 2023 Jul 25;12:e36121.
    PMID: 37490330 DOI: 10.2196/36121
    BACKGROUND: According to the World Bank, Malaysia reported an estimated 97 tuberculosis cases per 100,000 people in 2021. Chest x-ray (CXR) remains the best conventional method for the early detection of pulmonary tuberculosis (PTB) infection. The intervention of artificial intelligence (AI) in PTB diagnosis could efficiently aid human interpreters and reduce health professionals' work burden. To date, no AI studies have been evaluated in Malaysia.

    OBJECTIVE: This study aims to evaluate the performance of Putralytica and Qure.ai software for CXR screening and PTB diagnosis among the Malaysian population.

    METHODS: We will conduct a retrospective case-control study at the Respiratory Medicine Institute, National Cancer Institute, and Sungai Buloh Health Clinic. A total of 1500 CXR images of patients who completed treatments or check-ups will be selected and categorized into three groups: (1) abnormal PTB cases, (2) abnormal non-PTB cases, and (3) normal cases. These CXR images, along with their clinical findings, will be the reference standard in this study. All patient data, including sociodemographic characteristics and clinical history, will be collected prior to screening via Putralytica and Qure.ai software and readers' interpretation, which are the index tests for this study. Interpretation from all 3 index tests will be compared with the reference standard, and significant statistical analysis will be computed.

    RESULTS: Data collection is expected to commence in August 2023. It is anticipated that 1 year will be needed to conduct the study.

    CONCLUSIONS: This study will measure the accuracy of Putralytica and Qure.ai software and whether their findings will concur with readers' interpretation and the reference standard, thus providing evidence toward the effectiveness of implementing AI in the medical setting.

    INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/36121.

  9. Fulltext Effect of Online Reviews and Crowd Cues on Restaurant Choice of Customer: Moderating Role of Gender and Perceived Crowding
    Ali MA, Ting DH, Ahmad-Ur-Rahman M, Ali S, Shear F, Mazhar M
    Front Psychol, 2021;12:780863.
    PMID: 34925185 DOI: 10.3389/fpsyg.2021.780863
    This study is aimed to identify the relative (direct) effect of online review ratings and perceived crowding on purchase intentions of a consumer. Our study also investigated the contingent effect of gender and perceived crowding between the relationship of exogenous and endogenous variables. This study was conducted in the Malaysian restaurant industry. We applied the purposive sampling technique to identify respondents, the mall intercept survey method was used for data collection. Smart PLS software was applied for data analysis (200 respondents). This study demonstrates through its results that online review ratings and perceived crowding have a positive effect on purchase intentions of a consumer. Moreover, if a consumer perceives crowding at a restaurant, this has a positive contingent effect on the relationship between review ratings and purchase intentions. This demonstrates that the consumer is more inclined to choose a restaurant with a high online review rating and has high perceived crowding at some unfamiliar place. Lastly, no evidence is found for the gender difference between review rating and purchase intentions; however, gender shows contingent effect and results confirmed that males preferred more crowded restaurants as compared to females. There are theoretical and practical implications for managers in the findings of this study.
  10. Fulltext Stigma, Social Support, Illicit Drug Use, and Other Predictors of Anxiety and Depression Among HIV/AIDS Patients in Pakistan: A Cross-Sectional Study
    Ahmed A, Saqlain M, Umair MM, Hashmi FK, Saeed H, Amer M, et al.
    Front Public Health, 2021;9:745545.
    PMID: 34660521 DOI: 10.3389/fpubh.2021.745545
    Introduction: Anxiety and depression in people living with HIV/AIDS (PLWHA) can lead to non-adherence to antiretroviral therapy (ART), morbidity, and mortality. Therefore, assessing the stigma, social support, and other determinants of anxiety and depression in PLWHA are important for developing further interventions. Methods: An institution-based cross-sectional study was conducted in 505 PLWHA, approached through systematic sampling, who paid routine visits to the ART center, Pakistan Institute of Medical Sciences (PIMS), Islamabad. Data was collected by pretested validated hospital anxiety and depression scale (HADS). Version 26 of the SPSS was used to apply Logistic regression analysis to identify determinants, and the 95% confidence interval (CI) adjusted odds ratio (AOR) was calculated to assess the magnitude of the relationships. Results: In PLWHA, the prevalence of co-morbid depression and anxiety was 80%. Separately, 89.9% had depression, and 80.3% had anxiety. Use of illicit drugs [AOR = 1.87, 95% CI (1.01, 3.27)], low social support [AOR = 1.21, 95% CI (1.02, 2.25)], being male [AOR = 2.21, 95% CI (1.11, 5.49)], and HIV related stigma [AOR = 2.48, 95% CI (1.25, 6.02)] were significant predictors of depression. Having detectable viral load [AOR = 3.04, 95% CI (1.04, 8.86)], young age [AOR = 5.31, 95% CI (1.19, 29.39)], no formal education [AOR = 21.78, 95% CI (4.03, 117.62)], low [AOR = 1.70, 95% CI (1.12, 6.93)] or moderate [AOR = 2.20, 95% CI (1.79, 6.09)] social support, illicit drugs addiction [AOR = 1.17, 95% CI (1.03, 2.55)], and HIV stigma [AOR = 54.3, 95% CI (21.20, 139.32)] had a remarkable association with anxiety. Conclusions: Given the high prevalence of anxiety and depression among PLWHA, the Pakistan Ministry of Health should focus more on monitoring mental health, expanding mental health services, and developing interventions based on identified factors to treat depression and anxiety among PLWHA.
  11. Fulltext Entropy and Gaussian Filter-Based Adaptive Active Contour for Segmentation of Skin Lesions
    Mustafa S, Iqbal MW, Rana TA, Jaffar A, Shiraz M, Arif M, et al.
    Comput Intell Neurosci, 2022;2022:4348235.
    PMID: 35909861 DOI: 10.1155/2022/4348235
    Malignant melanoma is considered one of the deadliest skin diseases if ignored without treatment. The mortality rate caused by melanoma is more than two times that of other skin malignancy diseases. These facts encourage computer scientists to find automated methods to discover skin cancers. Nowadays, the analysis of skin images is widely used by assistant physicians to discover the first stage of the disease automatically. One of the challenges the computer science researchers faced when developing such a system is the un-clarity of the existing images, such as noise like shadows, low contrast, hairs, and specular reflections, which complicates detecting the skin lesions in that images. This paper proposes the solution to the problem mentioned earlier using the active contour method. Still, seed selection in the dynamic contour method has the main drawback of where it should start the segmentation process. This paper uses Gaussian filter-based maximum entropy and morphological processing methods to find automatic seed points for active contour. By incorporating this, it can segment the lesion from dermoscopic images automatically. Our proposed methodology tested quantitative and qualitative measures on standard dataset dermis and used to test the proposed method's reliability which shows encouraging results.
  12. Fulltext Boosting-based ensemble machine learning models for predicting unconfined compressive strength of geopolymer stabilized clayey soil
    Abdullah GMS, Ahmad M, Babur M, Badshah MU, Al-Mansob RA, Gamil Y, et al.
    Sci Rep, 2024 Jan 28;14(1):2323.
    PMID: 38282061 DOI: 10.1038/s41598-024-52825-7
    The present research employs new boosting-based ensemble machine learning models i.e., gradient boosting (GB) and adaptive boosting (AdaBoost) to predict the unconfined compressive strength (UCS) of geopolymer stabilized clayey soil. The GB and AdaBoost models were developed and validated using 270 clayey soil samples stabilized with geopolymer, with ground-granulated blast-furnace slag and fly ash as source materials and sodium hydroxide solution as alkali activator. The database was randomly divided into training (80%) and testing (20%) sets for model development and validation. Several performance metrics, including coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE), and mean squared error (MSE), were utilized to assess the accuracy and reliability of the developed models. The statistical results of this research showed that the GB and AdaBoost are reliable models based on the obtained values of R2 (= 0.980, 0.975), MAE (= 0.585, 0.655), RMSE (= 0.969, 1.088), and MSE (= 0.940, 1.185) for the testing dataset, respectively compared to the widely used artificial neural network, random forest, extreme gradient boosting, multivariable regression, and multi-gen genetic programming based models. Furthermore, the sensitivity analysis result shows that ground-granulated blast-furnace slag content was the key parameter affecting the UCS.
  13. Fulltext Rapamycin as a potent and selective inhibitor of vascular endothelial growth factor receptor in breast carcinoma
    Muhammad Sakri MS, Tengku Din TADA, Jaafar H, Gopalan V, Wan Abdul Rahman WF
    Int J Immunopathol Pharmacol, 2022;36:20587384211059673.
    PMID: 35037503 DOI: 10.1177/20587384211059673
    Angiogenesis is the process of new vascular formation, which is derived from various factors. For suppressing cancer cell growth, targeting angiogenesis is one of the therapeutic approaches. Vascular endothelial growth factor family receptors, including Flt-1, Flk-1 and Flt-4, have been found to play an essential role in regulating angiogenesis. Rapamycin is a macrolide compound with anti-proliferative properties, while platelet factor-4 (PF-4) is an antiangiogenic ELR-negative chemokine. Rapamycin inhibits mTOR ligands activation, thus suppressing cell proliferation, while PF-4 inhibits cell proliferation through several mechanisms. In the present study, we evaluated the effects of rapamycin and platelet factor-4 toward breast carcinoma at the proteomic and genomic levels. A total of 60 N-Methyl-N-Nitrosourea-induced rat breast carcinomas were treated with rapamycin, platelet factor-4 and rapamycin+platelet factor-4. The tumours were subsequently subjected to immunohistochemical protein analysis and polymerase chain reaction gene analysis. Protein analysis was performed using a semiquantitative scoring method, while the mRNA expression levels were analysed based on the relative expression ratio. There was a significant difference in the protein and mRNA expression levels for the selected markers. In the rapamycin+platelet factor-4-treated group, the Flt-4 marker was downregulated, whereas there were no differences in the expression levels of other markers, such as Flt-1 and Flk-1. On the other hand, platelet factor-4 did not exhibit a superior angiogenic inhibiting ability in this study. Rapamycin is a potent antiangiogenic drug; however, platelet factor-4 proved to be a less effective drug of anti-angiogenesis on rat breast carcinoma model.
  14. Fulltext Investigation on three-dimensional printed prosthetics leg sockets coated with different reinforcement materials: analysis on mechanical strength and microstructural
    Ramlee MH, Ammarullah MI, Mohd Sukri NS, Faidzul Hassan NS, Baharuddin MH, Abdul Kadir MR
    Sci Rep, 2024 Mar 21;14(1):6842.
    PMID: 38514731 DOI: 10.1038/s41598-024-57454-8
    Previous research has primarily focused on pre-processing parameters such as design, material selection, and printing techniques to improve the strength of 3D-printed prosthetic leg sockets. However, these methods fail to address the major challenges that arise post-printing, namely failures at the distal end of the socket and susceptibility to shear failure. Addressing this gap, the study aims to enhance the mechanical properties of 3D-printed prosthetic leg sockets through post-processing techniques. Fifteen PLA + prosthetic leg sockets are fabricated and reinforced with four materials: carbon fiber, carbon-Kevlar fiber, fiberglass, and cement. Mechanical and microstructural properties of the sockets are evaluated through axial compression testing and scanning electron microscopy (SEM). Results highlight superior attributes of cement-reinforced sockets, exhibiting significantly higher yield strength (up to 89.57% more than counterparts) and higher Young's modulus (up to 76.15% greater). SEM reveals correlations between microstructural properties and socket strength. These findings deepen the comprehension of 3D-printed prosthetic leg socket post-processing, presenting optimization prospects. Future research can focus on refining fabrication techniques, exploring alternative reinforcement materials, and investigating the long-term durability and functionality of post-processed 3D-printed prosthetic leg sockets.
  15. Giardia lamblia Immunoassay: Systematic review and meta-analysis
    Aziz AFE, Roshidi N, Muhammad Hanif MDH, Tye GJ, Arifin N
    Clin Chim Acta, 2024 Jul 15;561:119839.
    PMID: 38964570 DOI: 10.1016/j.cca.2024.119839
    Immunoassays are important tools in diagnosing giardiasis, though there are several controversies inherent in the existing methods. We conducted a systematic review and meta-analysis to assess the pooled diagnostic accuracy of immunoassays in detecting the gastrointestinal disease-causing parasite Giardia lamblia. Our comprehensive search, which included PubMed, Scopus, and ScienceDirect from 2000 up until 2023, resulted in 34 studies reporting the performance of 24 different immunoassays. The overall pooled sensitivity and specificity of immunoassays and subgroup analyses were determined. Notably, ImmunoCardSTAT® and RIDASCREEN® Giardia were the most used assays (n = 6 studies each). They exhibited sensitivity and specificity of 84 % and 99 % and 93 % and 99 %, respectively. Sub-group analysis on the type of immunoassays (without the case-control studies) showed that commercial ELISA had higher sensitivity (96 %) compared to a commercial immunochromatographic (88 %), which justifies the difference of sensitivity between ImmunoCardSTAT® and RIDASCREEN® Giardia. However, the applicability between these two in clinical settings, replacing the gold standard, should be considered including the time, equipment requirement, and budget. Samples from symptomatic patients showed higher sensitivity (92 %) compared to asymptomatic patients (79 %). Overall, immunoassays can be a practical replacement for the current gold standard, but more information should be gathered regarding the cost of providing more conclusive suggestions on these findings.
  16. Fulltext Waste management and green technology: future trends in circular economy leading towards environmental sustainability
    Tanveer M, Khan SAR, Umar M, Yu Z, Sajid MJ, Haq IU
    Environ Sci Pollut Res Int, 2022 Nov;29(53):80161-80178.
    PMID: 36197607 DOI: 10.1007/s11356-022-23238-8
    The effective treatment of waste to be used as a resource in future has a major role in achieving environmental sustainability and moving towards circular economy. The current research is aimed to provide in-depth detail regarding prominent trends and research themes, evolution, future research orientation, main characteristics, and mapping of research publications on waste management, technological innovation in circular economy domain from the year 2000 to 2021. Different analyses including text mining and bibliometric and content analyses were applied to answer the research question and provide the details on aforementioned variables. From the bibliometric analyses, a total of 1118 articles were drawn out from the Scopus database to conceptualize the core body of research. As a result, the following themes were identified: electronic waste, circular economy transition, plastic waste, bio-based waste management, lifecycle assessment, and ecological impacts, and construction and demolition waste management. The highlighted features, future research orientation, and prominent research perspective can provide guideline for future research to enrich the literature through conducting studies on provided research directions and help lead waste management and technological innovation policymakers, professionals, and practitioners in moving towards circular transition.
  17. Artificial neural network modeling for the prediction, estimation, and treatment of diverse wastewaters: A comprehensive review and future perspective
    Ibrahim M, Haider A, Lim JW, Mainali B, Aslam M, Kumar M, et al.
    Chemosphere, 2024 Jul 15;362:142860.
    PMID: 39019174 DOI: 10.1016/j.chemosphere.2024.142860
    The application of artificial neural networks (ANNs) in the treatment of wastewater has achieved increasing attention, as it enhances the efficiency and sustainability of wastewater treatment plants (WWTPs). This paper explores the application of ANN-based models in WWTPs, focusing on the latest published research work, by presenting the effectiveness of ANNs in predicting, estimating, and treatment of diverse types of wastewater. Furthermore, this review comprehensively examines the applicability of the ANNs in various processes and methods used for wastewater treatment, including membrane and membrane bioreactors, coagulation/flocculation, UV-disinfection processes, and biological treatment systems. Additionally, it provides a detailed analysis of pollutants viz organic and inorganic substances, nutrients, pharmaceuticals, drugs, pesticides, dyes, etc., from wastewater, utilizing both ANN and ANN-based models. Moreover, it assesses the techno-economic value of ANNs, provides cost estimation and energy analysis, and outlines promising future research directions of ANNs in wastewater treatment. AI-based techniques are used to predict parameters such as chemical oxygen demand (COD) and biological oxygen demand (BOD) in WWTP influent. ANNs have been formed for the estimation of the removal efficiency of pollutants such as total nitrogen (TN), total phosphorus (TP), BOD, and total suspended solids (TSS) in the effluent of WWTPs. The literature also discloses the use of AI techniques in WWT is an economical and energy-effective method. AI enhances the efficiency of the pumping system, leading to energy conservation with an impressive average savings of approximately 10%. The system can achieve a maximum energy savings state of 25%, accompanied by a notable reduction in costs of up to 30%.
  18. Fulltext Dataset of taxonomic identification from surface water in the coastal area of Peninsular Malaysia
    Khairul Anuar AN, Muhammad Zamri NK, Mohd Yuzaidey MA, Su Nyun Pau S, Mustaffa NIH
    Data Brief, 2024 Aug;55:110683.
    PMID: 39071957 DOI: 10.1016/j.dib.2024.110683
    This article describes the abundance of phytoplankton community structures in Port Dickson, Negeri Sembilan and Pulau Tinggi, Johor during the Southwest and Northeast Monsoons and includes data from 48 selected sampling sites collected between July and December 2023. The seawater samples from 1-meter depth were obtained by using a Niskin water sampler, concentrated in a 50 ml centrifuge tube and immediately preserved with Lugol's iodine solution. The data include phytoplankton density (cell L-1), the total density of phytoplankton in each station, and the total number of genera obtained in every station. Additional data are presented, including chlorophyll-a concentration, as a proxy for biomass and photosynthetic active radiation. This article presents data on 30 genera, including unidentified genera, as well as the percentage of the main community group.
  19. Fulltext Co-movement of energy prices and stock market return: environmental wavelet nexus of COVID-19 pandemic from the USA, Europe, and China
    Chien F, Sadiq M, Kamran HW, Nawaz MA, Hussain MS, Raza M
    Environ Sci Pollut Res Int, 2021 Feb 23;28(25):32359-73.
    PMID: 33624244 DOI: 10.1007/s11356-021-12938-2
    This work aims to study the time-frequency relationship between the recent COVID-19 pandemic and instabilities in oil price and the stock market, geopolitical risks, and uncertainty in the economic policy in the USA, Europe, and China. The coherence wavelet method and the wavelet-based Granger causality tests are applied to the data (31st December 2019 to 1st August 2020) based on daily COVID-19 observations, oil prices, US-EPU, the US geopolitical risk index, and the US stock price index. The short- and long-term COVID-19 consequences are depicted differently and may initially be viewed as an economic crisis. The results illustrate the reduced industrial productivity, which intensifies with the increase in the pandemic's severeness (i.e., a 10.57% decrease in the productivity index with a 1% increase in the pandemic severeness). Similarly, indices for oil demand, stock market, GDP growth, and electricity demand decrease significantly with an increase in the pandemic severeness index (i.e., a 1% increase in the pandemic severeness results in a 0.9%, 0.67%, 1.12%, and 0.65% decrease, respectively). However, the oil market shows low co-movement with the stock exchange, exchange rate, and gold markets. Therefore, investors and the government are recommended to invest in the oil market to generate revenue during the sanctions period.
  20. Fulltext Multi-Omics Approaches and Resources for Systems-Level Gene Function Prediction in the Plant Kingdom
    Abdullah-Zawawi MR, Govender N, Harun S, Muhammad NAN, Zainal Z, Mohamed-Hussein ZA
    Plants (Basel), 2022 Oct 05;11(19).
    PMID: 36235479 DOI: 10.3390/plants11192614
    In higher plants, the complexity of a system and the components within and among species are rapidly dissected by omics technologies. Multi-omics datasets are integrated to infer and enable a comprehensive understanding of the life processes of organisms of interest. Further, growing open-source datasets coupled with the emergence of high-performance computing and development of computational tools for biological sciences have assisted in silico functional prediction of unknown genes, proteins and metabolites, otherwise known as uncharacterized. The systems biology approach includes data collection and filtration, system modelling, experimentation and the establishment of new hypotheses for experimental validation. Informatics technologies add meaningful sense to the output generated by complex bioinformatics algorithms, which are now freely available in a user-friendly graphical user interface. These resources accentuate gene function prediction at a relatively minimal cost and effort. Herein, we present a comprehensive view of relevant approaches available for system-level gene function prediction in the plant kingdom. Together, the most recent applications and sought-after principles for gene mining are discussed to benefit the plant research community. A realistic tabulation of plant genomic resources is included for a less laborious and accurate candidate gene discovery in basic plant research and improvement strategies.
Related Terms
Filters
Contact Us

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

External Links