Displaying publications 1 - 20 of 72 in total

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  1. Fabrication of Fucoxanthin-Loaded Microsphere(F-LM) By Two Steps Double-Emulsion Solvent Evaporation Method and Characterization of Fucoxanthin before and after Microencapsulation
    Noviendri D, Jaswir I, Taher M, Mohamed F, Salleh HM, Noorbatcha IA, et al.
    J Oleo Sci, 2016 Jul 15.
    PMID: 27430384
    Microencapsulation is a promising approach in drug delivery to protect the drug from degradation and allow controlled release of the drug in the body. Fucoxanthin-loaded microsphere (F-LM) was fabricated by two step w/o/w double emulsion solvent evaporation method with poly (L-lactic-co-glycolic acid) (PLGA) as carrier. The effect of four types of surfactants (PVA, Tween-20, Span-20 and SDS), homogenization speed, and concentration of PLGA polymer and surfactant (PVA), respectively, on particle size and morphology of F-LM were investigated. Among the surfactants tested, PVA showed the best results with smallest particle size (9.18 µm) and a smooth spherical surface. Increasing the homogenization speed resulted in a smaller mean F-LM particle size [d(0.50)] from 17.12 to 9.18 µm. Best particle size results and good morphology were attained at homogenization speed of 20 500 rpm. Meanwhile, increased PLGA concentration from 1.5 to 11.0 (% w/v) resulted in increased F-LM particle size. The mean particle size [d(0.5)] of F-LM increased from 3.93 to 11.88 µm. At 6.0 (% w/v) PLGA, F-LM showed the best structure and external morphology. Finally, increasing PVA concentration from 0.5 to 3.5 (% w/v) resulted in decreased particle size from 9.18 to 4.86 µm. Fucoxanthin characterization before and after microencapsulation was carried out to assess the success of the microencapsulation procedure. Thermo gravimetry analysis (TGA), glass transition (Tg) temperature of F-LM and fucoxanthin measured using DSC, ATR-FTIR and XRD indicated that fucoxanthin was successfully encapsulated into the PLGA matrix, while maintaining the structural and chemical integrity of fucoxanthin.
  2. Fulltext An Intelligent Proposed Model for Task Offloading in Fog-Cloud Collaboration Using Logistics Regression
    Bukhari MM, Ghazal TM, Abbas S, Khan MA, Farooq U, Wahbah H, et al.
    Comput Intell Neurosci, 2022;2022:3606068.
    PMID: 35126487 DOI: 10.1155/2022/3606068
    Smart applications and intelligent systems are being developed that are self-reliant, adaptive, and knowledge-based in nature. Emergency and disaster management, aerospace, healthcare, IoT, and mobile applications, among them, revolutionize the world of computing. Applications with a large number of growing devices have transformed the current design of centralized cloud impractical. Despite the use of 5G technology, delay-sensitive applications and cloud cannot go parallel due to exceeding threshold values of certain parameters like latency, bandwidth, response time, etc. Middleware proves to be a better solution to cope up with these issues while satisfying the high requirements task offloading standards. Fog computing is recommended middleware in this research article in view of the fact that it provides the services to the edge of the network; delay-sensitive applications can be entertained effectively. On the contrary, fog nodes contain a limited set of resources that may not process all tasks, especially of computation-intensive applications. Additionally, fog is not the replacement of the cloud, rather supplement to the cloud, both behave like counterparts and offer their services correspondingly to compliance the task needs but fog computing has relatively closer proximity to the devices comparatively cloud. The problem arises when a decision needs to take what is to be offloaded: data, computation, or application, and more specifically where to offload: either fog or cloud and how much to offload. Fog-cloud collaboration is stochastic in terms of task-related attributes like task size, duration, arrival rate, and required resources. Dynamic task offloading becomes crucial in order to utilize the resources at fog and cloud to improve QoS. Since this formation of task offloading policy is a bit complex in nature, this problem is addressed in the research article and proposes an intelligent task offloading model. Simulation results demonstrate the authenticity of the proposed logistic regression model acquiring 86% accuracy compared to other algorithms and confidence in the predictive task offloading policy by making sure process consistency and reliability.
  3. Fulltext Fischer Linear Discrimination and Quadratic Discrimination Analysis-Based Data Mining Technique for Internet of Things Framework for Healthcare
    Hasan MK, Ghazal TM, Alkhalifah A, Abu Bakar KA, Omidvar A, Nafi NS, et al.
    Front Public Health, 2021;9:737149.
    PMID: 34712639 DOI: 10.3389/fpubh.2021.737149
    The internet of reality or augmented reality has been considered a breakthrough and an outstanding critical mutation with an emphasis on data mining leading to dismantling of some of its assumptions among several of its stakeholders. In this work, we study the pillars of these technologies connected to web usage as the Internet of things (IoT) system's healthcare infrastructure. We used several data mining techniques to evaluate the online advertisement data set, which can be categorized as high dimensional with 1,553 attributes, and the imbalanced data set, which automatically simulates an IoT discrimination problem. The proposed methodology applies Fischer linear discrimination analysis (FLDA) and quadratic discrimination analysis (QDA) within random projection (RP) filters to compare our runtime and accuracy with support vector machine (SVM), K-nearest neighbor (KNN), and Multilayer perceptron (MLP) in IoT-based systems. Finally, the impact on number of projections was practically experimented, and the sensitivity of both FLDA and QDA with regard to precision and runtime was found to be challenging. The modeling results show not only improved accuracy, but also runtime improvements. When compared with SVM, KNN, and MLP in QDA and FLDA, runtime shortens by 20 times in our chosen data set simulated for a healthcare framework. The RP filtering in the preprocessing stage of the attribute selection, fulfilling the model's runtime, is a standpoint in the IoT industry. Index Terms: Data Mining, Random Projection, Fischer Linear Discriminant Analysis, Online Advertisement Dataset, Quadratic Discriminant Analysis, Feature Selection, Internet of Things.
  4. Fulltext Apoptosis, antimicrobial and antioxidant activities of phytochemicals from Garcinia malaccensis Hk.f
    Taher M, Susanti D, Rezali MF, Zohri FS, Ichwan SJ, Alkhamaiseh SI, et al.
    Asian Pac J Trop Med, 2012 Feb;5(2):136-41.
    PMID: 22221758 DOI: 10.1016/S1995-7645(12)60012-1
    OBJECTIVE: To study the chemical constituents of stembark of Garcinia malaccensis (G. malaccensis) together with apoptotic, antimicrobial and antioxidant activities.

    METHODS: Purification and structure elucidation were carried out by chromatographic and spectroscopic techniques, respectively. MTT and trypan blue exclusion methods were performed to study the cytotoxic activity. Antibacterial activity was conducted by disc diffusion and microdilution methods, whereas antioxidant activities were done by ferric thiocyanate method and DPPH radical scavenging.

    RESULTS: The phytochemical study led to the isolation of α,β-mangostin and cycloart-24-en-3β-ol. α-Mangostin exhibited cytotoxic activity against HSC-3 cells with an IC(50) of 0.33 μM. β- and α-mangostin showed activity against K562 cells with IC(50) of 0.40 μM and 0.48 μM, respectively. α-Mangostin was active against Gram-positive bacteria, Staphylococcus aureus (S. aureus) and Bacillus anthracis (B. anthracis) with inhibition zone and MIC value of (19 mm; 0.025 mg/mL) and (20 mm; 0.013 mg/mL), respectively. In antioxidant assay, α-mangostin exhibited activity as an inhibitor of lipid peroxidation.

    CONCLUSIONS: G. malaccensis presence α- and β-mangostin and cycloart-24-en-3β-ol. β-Mangostin was found very active against HSC-3 cells and K562. The results suggest that mangostins derivatives have the potential to inhibit the growth of cancer cells by inducing apoptosis. In addition, α-and β-mangostin was found inhibit the growth of Gram-positive pathogenic bacteria and also showed the activity as an inhibitor of lipid peroxidation.

  5. A lignan with glucose uptake activity in 3T3-L1 adipocytes from the stem bark of Knema patentinervia
    Taher M, Amiroudine MZAM, Jaffri JM, Amri MS, Susanti D, Abd Hamid S, et al.
    Pak J Pharm Sci, 2017 Jul;30(4):1335-1339.
    PMID: 29039334
    A new naturally occurring dibenzylbutyrolactone lignan named isocubebinic ether has been isolated from Knema patentinervia. The structure was established by spectroscopic methods, which include Ultraviolet, Infrared, Nuclear Magnetic Resonance and Mass Spectrometry. The compound showed activity in the stimulation of glucose uptake by 3T3-L1 adipocytes.
  6. Fulltext An IoMT-Enabled Smart Healthcare Model to Monitor Elderly People Using Machine Learning Technique
    Khan MF, Ghazal TM, Said RA, Fatima A, Abbas S, Khan MA, et al.
    Comput Intell Neurosci, 2021;2021:2487759.
    PMID: 34868288 DOI: 10.1155/2021/2487759
    The Internet of Medical Things (IoMT) enables digital devices to gather, infer, and broadcast health data via the cloud platform. The phenomenal growth of the IoMT is fueled by many factors, including the widespread and growing availability of wearables and the ever-decreasing cost of sensor-based technology. The cost of related healthcare will rise as the global population of elderly people grows in parallel with an overall life expectancy that demands affordable healthcare services, solutions, and developments. IoMT may bring revolution in the medical sciences in terms of the quality of healthcare of elderly people while entangled with machine learning (ML) algorithms. The effectiveness of the smart healthcare (SHC) model to monitor elderly people was observed by performing tests on IoMT datasets. For evaluation, the precision, recall, fscore, accuracy, and ROC values are computed. The authors also compare the results of the SHC model with different conventional popular ML techniques, e.g., support vector machine (SVM), K-nearest neighbor (KNN), and decision tree (DT), to analyze the effectiveness of the result.
  7. Fulltext Profiling the Antidiabetic Potential of Compounds Identified from Fractionated Extracts of Entada africana toward Glucokinase Stimulation: Computational Insight
    Onikanni SA, Lawal B, Munyembaraga V, Bakare OS, Taher M, Khotib J, et al.
    Molecules, 2023 Jul 30;28(15).
    PMID: 37570723 DOI: 10.3390/molecules28155752
    Glucokinase plays an important role in regulating the blood glucose level and serves as an essential therapeutic target in type 2 diabetes management. Entada africana is a medicinal plant and highly rich source of bioactive ligands with the potency to develop new target drugs for glucokinase such as diabetes and obesity. Therefore, the study explored a computational approach to predict identified compounds from Entada africana following its intermolecular interactions with the allosteric binding site of the enzymes. We retrieved the three-dimensional (3D) crystal structure of glucokinase (PDB ID: 4L3Q) from the online protein data bank and prepared it using the Maestro 13.5, Schrödinger Suite 2022-3. The compounds identified were subjected to ADME, docking analysis, pharmacophore modeling, and molecular simulation. The results show the binding potential of the identified ligands to the amino acid residues, thereby suggesting an interaction of the amino acids with the ligand at the binding site of the glucokinase activator through conventional chemical bonds such as hydrogen bonds and hydrophobic interactions. The compatibility of the molecules was highly observed when compared with the standard ligand, thereby leading to structural and functional changes. Therefore, the bioactive components from Entada africana could be a good driver of glucokinase, thereby paving the way for the discovery of therapeutic drugs for the treatment of diabetes and its related complications.
  8. In vitro inhibitory effect of rubraxanthone isolated from Garcinia parvifolia on platelet-activating factor receptor binding
    Jantan I, Pisar MM, Idris MS, Taher M, Ali RM
    Planta Med, 2002 Dec;68(12):1133-4.
    PMID: 12494345
    Rubraxanthone and isocowanol isolated from Garcinia parvifolia Miq. were investigated for their inhibitory effects on platelet-activating factor (PAF) binding to rabbit platelets using 3H-PAF as a ligand. Rubraxanthone showed a strong inhibition with IC 50 value of 18.2 microM. The IC 50 values of macluraxanthone, 6-deoxyjacareubin, 2-(3-methylbut-2-enyl)-1,3,5-trihydroxyxanthone, 2-(3-methylbut-2-enyl)-1,3,5,6-tetrahydroxyxanthone and 1,3,5-trihydroxy-6,6'-dimethylpyrano(2',3':6,7)-4-(1,1-dimethylprop-2-enyl)-xanthone were also determined for comparison. In the course of our study on structure-activity relationship of xanthones, the results revealed that a geranyl group substituted at C-8 was beneficial to the binding while a hydroxylated prenyl group at C-4 resulted in a significant loss in binding to the PAF receptor.
  9. A polyisoprenylated ketone from Calophyllum enervosum
    Taher M, Idris MS, Ahmad F, Arbain D
    Phytochemistry, 2005 Mar;66(6):723-6.
    PMID: 15771897
    A polyisoprenylated ketone named enervosanone has been isolated from the stem bark of Calophyllum enervosum together with three known compounds, cambogin, osajaxanthone and epicatechin. Their structures were determined by spectroscopic analysis. The antimicrobial evaluations of the isolated compounds were also reported.
  10. Fulltext In vitro antimicrobial activity of mangrove plant Sonneratia alba
    Saad S, Taher M, Susanti D, Qaralleh H, Awang AF
    Asian Pac J Trop Biomed, 2012 Jun;2(6):427-9.
    PMID: 23569943 DOI: 10.1016/S2221-1691(12)60069-0
    To investigate the antimicrobial property of mangrove plant Sonneratia alba (S. alba).
  11. Fulltext Polygonumins A, a newly isolated compound from the stem of Polygonum minus Huds with potential medicinal activities
    Ahmad R, Sahidin I, Taher M, Low C, Noor NM, Sillapachaiyaporn C, et al.
    Sci Rep, 2018 03 09;8(1):4202.
    PMID: 29523802 DOI: 10.1038/s41598-018-22485-5
    Polygonumins A, a new compound, was isolated from the stem of Polygonum minus. Based on NMR results, the compound's structure is identical to that of vanicoside A, comprising four phenylpropanoid ester units and a sucrose unit. The structure differences were located at C-3″″'. The cytotoxic activity of polygonumins A was evaluated on several cancer cell lines by a cell viability assay using tetrazolium dye 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT). The compound showed the highest antiproliferative (p 
  12. Fulltext Methanol extract of Muntingia calabura leaves attenuates CCl4-induced liver injury: possible synergistic action of flavonoids and volatile bioactive compounds on endogenous defence system
    Zakaria ZA, Mahmood ND, Omar MH, Taher M, Basir R
    Pharm Biol, 2019 Dec;57(1):335-344.
    PMID: 31068038 DOI: 10.1080/13880209.2019.1606836
    CONTEXT: Muntingia calabura L. (Muntingiaceae) exerts antioxidant and anti-inflammatory activities, thus, it might be a good hepatoprotective agent.

    OBJECTIVE: This study investigates the effect of methanol extract of M. calabura leaves (MMCL) on hepatic antioxidant and anti-inflammatory activities in CCl4-induced hepatotoxic rat.

    MATERIALS AND METHODS: Sprague Dawley rats (n = 6) were treated (p.o.) with 10% DMSO (Groups 1 and 2), 50 mg/kg N-acetylcysteine (Group 3) or, 50, 250, or 500 mg/kg MMCL (Groups 4-6) for 7 consecutive days followed by pretreatment (i.p.) with vehicle (Group 1) or 50% CCl4 in olive oil (v/v) (Groups 2-6) on day 7th. Plasma liver enzymes and hepatic antioxidant enzymes and pro-inflammatory cytokines concentrations were measured while liver histopathology was examined.

    RESULTS: MMCL, at 500 mg/kg, significantly (p 

  13. Pregnant and severe acute abdominal pain: A surgical diagnostic dilemma
    Kosai NR, Amin-Tai H, Gendeh HS, Salleh S, Reynu R, Taher MM, et al.
    Clin Ter, 2015;166(3):110-3.
    PMID: 26152617 DOI: 10.7417/CT.2015.1839
    Acute abdominal pain in pregnancy remains a surgical conundrum. A 25-year-old primigravid at 29 weeks gestation presented with a two-week history of epigastric pain, nausea and vomiting. She had a distended abdomen consistent with a full term gravid uterus; tender at the epigastric and right hypochondrium suggestive of small bowel obstruction or acute appendicitis. Abdominal ultrasound was inconclusive but abdominal Computed Tomography (CT) suggested small bowel volvulus. An exploratory laparotomy revealed a segmental jejunal volvulus and small bowel diverticulum contributing to the volvulus. A short segmental bowel resection was performed. Histopathology confirmed a Meckel's Diverticulum. The patient recovered well but underwent premature labour 10 days later. Small bowel obstruction secondary to Meckel's diverticulum is rare in pregnancy. In an acute gestational abdomen, clinical examination is key. Radiological imaging may be helpful, whilst surgical intervention is confirmatory and therapeutic in the event of an obstructive volvulus.
  14. Effect of Exercise on Pulmonary Function Tests in Obese Malaysian Patients
    Christopher LK, Kosai NR, Reynu R, Levin KB, Taher MM, Sutton PA, et al.
    Clin Ter, 2015;166(3):105-9.
    PMID: 26152616 DOI: 10.7417/CT.2015.1838
    Obesity has taken the 21st century by storm, posing negative effects on of the various facades of health, healthcare and global economy. With regards to pulmonary performance, numerous studies have proven the detrimental effects of obesity while reinstating the positive effects of weight loss on overall pulmonary function. However, effects of exercise on pulmonary function and correlation between changes in pulmonary function test with weight loss have yet to be described. We performed a prospective interventional study to determine the effects of regular exercise on Pulmonary Function Tests (PFT) and ascertain the relationship between weight loss and change in PFT in obese patients.
  15. Fulltext Electrosprayed Alginate Nanoparticles as CRISPR Plasmid DNA Delivery Carrier: Preparation, Optimization, and Characterization
    Alallam B, Altahhan S, Taher M, Mohd Nasir MH, Doolaanea AA
    Pharmaceuticals (Basel), 2020 Jul 22;13(8).
    PMID: 32707857 DOI: 10.3390/ph13080158
    Therapeutic gene editing is becoming more feasible with the emergence of the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated protein (Cas) system. However, the successful implementation of CRISPR/Cas9-based therapeutics requires a safe and efficient in vivo delivery of the CRISPR components, which remains challenging. This study presents successful preparation, optimization, and characterization of alginate nanoparticles (ALG NPs), loaded with two CRISPR plasmids, using electrospray technique. The aim of this delivery system is to edit a target gene in another plasmid (green fluorescent protein (GFP)). The effect of formulation and process variables were evaluated. CRISPR ALG NPs showed mean size and zeta potential of 228 nm and -4.42 mV, respectively. Over 99.0% encapsulation efficiency was achieved while preserving payload integrity. The presence of CRISPR plasmids in the ALG NPs was confirmed by Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy. The tests revealed that the nanoparticles were cytocompatible and successfully introduced the Cas9 transgene in HepG2 cells. Nanoparticles-transfected HepG2 was able to edit its target plasmid by introducing double-strand break (DSB) in GFP gene, indicating the bioactivity of CRISPR plasmids encapsulated in alginate nanoparticles. This suggests that this method is suitable for biomedical application in vitro or ex vivo. Future investigation of theses nanoparticles might result in nanocarrier suitable for in vivo delivery of CRISPR/Cas9 system.
  16. Fulltext Creative treatment of early buried bumper syndrome
    Taher MM, Kosai NR, Gendeh HS
    Ann R Coll Surg Engl, 2014 Nov;96(8):621-2.
    PMID: 25350188 DOI: 10.1308/rcsann.2014.96.8.621b
  17. Fulltext RETRACTED ARTICLE: Positioning of UAV Base Stations Using 5G and Beyond Networks for IoMT Applications
    Ghazal TM
    Arab J Sci Eng, 2023;48(4):5687.
    PMID: 34367874 DOI: 10.1007/s13369-021-05985-x
  18. Fulltext Optimized Visual Internet of Things for Video Streaming Enhancement in 5G Sensor Network Devices
    Budati AK, Islam S, Hasan MK, Safie N, Bahar N, Ghazal TM
    Sensors (Basel), 2023 May 25;23(11).
    PMID: 37299798 DOI: 10.3390/s23115072
    The global expansion of the Visual Internet of Things (VIoT)'s deployment with multiple devices and sensor interconnections has been widespread. Frame collusion and buffering delays are the primary artifacts in the broad area of VIoT networking applications due to significant packet loss and network congestion. Numerous studies have been carried out on the impact of packet loss on Quality of Experience (QoE) for a wide range of applications. In this paper, a lossy video transmission framework for the VIoT considering the KNN classifier merged with the H.265 protocols. The performance of the proposed framework was assessed while considering the congestion of encrypted static images transmitted to the wireless sensor networks. The performance analysis of the proposed KNN-H.265 protocol is compared with the existing traditional H.265 and H.264 protocols. The analysis suggests that the traditional H.264 and H.265 protocols cause video conversation packet drops. The performance of the proposed protocol is estimated with the parameters of frame number, delay, throughput, packet loss ratio, and Peak Signal to Noise Ratio (PSNR) on MATLAB 2018a simulation software. The proposed model gives 4% and 6% better PSNR values than the existing two methods and better throughput.
  19. Fulltext FUZ-SMO: A fuzzy slime mould optimizer for mitigating false alarm rates in the classification of underwater datasets using deep convolutional neural networks
    Liang Zhang D, Jiang Z, Mohammadzadeh F, Hasani Azhdari SM, Abualigah L, Ghazal TM
    Heliyon, 2024 Apr 15;10(7):e28681.
    PMID: 38586386 DOI: 10.1016/j.heliyon.2024.e28681
    Sonar sound datasets are of significant importance in the domains of underwater surveillance and marine research as they enable experts to discern intricate patterns within the depths of the water. Nevertheless, the task of classifying sonar sound datasets continues to pose significant challenges. In this study, we present a novel approach aimed at enhancing the precision and efficacy of sonar sound dataset classification. The integration of deep long-short-term memory (DLSTM) and convolutional neural networks (CNNs) models is employed in order to capitalize on their respective advantages while also utilizing distinctive feature engineering techniques to achieve the most favorable outcomes. Although DLSTM networks have demonstrated effectiveness in tasks involving sequence classification, attaining their optimal performance necessitates careful adjustment of hyperparameters. While traditional methods such as grid and random search are effective, they frequently encounter challenges related to computational inefficiencies. This study aims to investigate the unexplored capabilities of the fuzzy slime mould optimizer (FUZ-SMO) in the context of LSTM hyperparameter tuning, with the objective of addressing the existing research gap in this area. Drawing inspiration from the adaptive behavior exhibited by slime moulds, the FUZ-SMO proposes a novel approach to optimization. The amalgamated model, which combines CNN, LSTM, fuzzy, and SMO, exhibits a notable improvement in classification accuracy, outperforming conventional LSTM architectures by a margin of 2.142%. This model not only demonstrates accelerated convergence milestones but also displays significant resilience against overfitting tendencies.
  20. Fulltext Apoptotic Activity of New Oxisterigmatocystin Derivatives from the Marine-Derived Fungus Aspergillus nomius NC06
    Artasasta MA, Yanwirasti Y, Taher M, Djamaan A, Ariantari NP, Edrada-Ebel RA, et al.
    Mar Drugs, 2021 Nov 11;19(11).
    PMID: 34822502 DOI: 10.3390/md19110631
    Sponge-derived fungi have recently attracted attention as an important source of interesting bioactive compounds. Aspergillus nomius NC06 was isolated from the marine sponge Neopetrosia chaliniformis. This fungus was cultured on rice medium and yielded four compounds including three new oxisterigmatocystins, namely, J, K, and L (1, 2, and 3), and one known compound, aspergillicin A (4). Structures of the compounds were elucidated by 1D and 2D NMR spectroscopy and by high-resolution mass spectrometry. The isolated compounds were tested for cytotoxic activity against HT 29 colon cancer cells, where compounds 1, 2, and 4 exhibited IC50 values of 6.28, 15.14, and 1.63 µM, respectively. Under the fluorescence microscope by using a double staining method, HT 29 cells were observed to be viable, apoptotic, and necrotic after treatment with the cytotoxic compounds 1, 2, and 4. The result shows that compounds 1 and 2 were able to induce apoptosis and cell death in HT 29 cells.
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