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  1. Optimal control strategies for SGLT2 inhibitors as a novel anti-tumor agent and their effect on human breast cancer cells with the effect of time delay and hyperglycemia
    Alblowy AH, Maan N, Ibrahim AA
    Comput Biol Med, 2023 Oct 05;166:107552.
    PMID: 37826954 DOI: 10.1016/j.compbiomed.2023.107552
    Breast cancer is the most frequent cancer in the world, and it continues to have a significant impact on the total number of cancer deaths. Recently, oncology findings hint at the role of excessive glucose in cancer progression and immune cells' suppression. Sequel to this revelation is ongoing researches on possible inhibition of glucose flow into the tumor micro-environment as therapeutics for malignant treatment. In this study, the effect of glucose blockage therapeutics such as SGLT-2 inhibitors drug on the dynamics of normal, tumors and immune cells interaction is mathematically studied. The asymptomatic nature of the breast cancer is factored into the model using time delay. We first investigate the boundedness and non-negativity of the solution. The condition for existence of critical equilibrium point is determined, and its global stability conditions are derived using Lyapunov function. This revealed that a timely administration of the SGLT-2 inhibitors drug can eliminate tumor cells. Secondly, we determine the sufficient and necessary conditions for optimal control strategy of SGLT-2 inhibitors so as to avert side effects on normal cells using a Pontryagin's Minimum Principle. The results showed that if the ingestion rate of the inhibitor drug is equal to the digestion rate, the tumor cells can be completely eliminated within 9 months without side effects. The analytical results were numerically verified and the qualitative views of interacting cells dynamics is showcased.
  2. Fulltext Optimal battery sizing in photovoltaic based distributed generation using enhanced opposition-based firefly algorithm for voltage rise mitigation
    Wong LA, Shareef H, Mohamed A, Ibrahim AA
    ScientificWorldJournal, 2014;2014:752096.
    PMID: 25054184 DOI: 10.1155/2014/752096
    This paper presents the application of enhanced opposition-based firefly algorithm in obtaining the optimal battery energy storage systems (BESS) sizing in photovoltaic generation integrated radial distribution network in order to mitigate the voltage rise problem. Initially, the performance of the original firefly algorithm is enhanced by utilizing the opposition-based learning and introducing inertia weight. After evaluating the performance of the enhanced opposition-based firefly algorithm (EOFA) with fifteen benchmark functions, it is then adopted to determine the optimal size for BESS. Two optimization processes are conducted where the first optimization aims to obtain the optimal battery output power on hourly basis and the second optimization aims to obtain the optimal BESS capacity by considering the state of charge constraint of BESS. The effectiveness of the proposed method is validated by applying the algorithm to the 69-bus distribution system and by comparing the performance of EOFA with conventional firefly algorithm and gravitational search algorithm. Results show that EOFA has the best performance comparatively in terms of mitigating the voltage rise problem.
  3. Indole-7-carbaldehyde thiosemicarbazone as a flexidentate ligand toward ZnII, CdII, PdII and PtII ions: cytotoxic and apoptosis-inducing properties of the PtII complex
    Ibrahim AA, Khaledi H, Hassandarvish P, Mohd Ali H, Karimian H
    Dalton Trans, 2014 Mar 14;43(10):3850-60.
    PMID: 24442181 DOI: 10.1039/c3dt53032a
    A new thiosemicarbazone (LH2) derived from indole-7-carbaldehyde was synthesized and reacted with Zn(II), Cd(II), Pd(II) and Pt(II) salts. The reactions with zinc and cadmium salts in 2 : 1 (ligand-metal) molar ratio afforded complexes of the type MX2(LH2)2, (X = Cl, Br or OAc), in which the thiosemicarbazone acts as a neutral S-monodentate ligand. In the presence of potassium hydroxide, the reaction of LH2 with ZnBr2 resulted in deprotonation of the thiosemicarbazone at the hydrazine and indole nitrogens to form Zn(L)(CH3OH). The reaction of LH2 with K2PdCl4 in the presence of triethylamine, afforded Pd(L)(LH2) which contains two thiosemicarbazone ligands: one being dianionic N,N,S-tridentate while the other one is neutral S-monodentate. When PdCl2(PPh3)2 was used as the Pd(II) ion source, Pd(L)(PPh3) was obtained. In a similar manner, the analogous platinum complex, Pt(L)(PPh3), was synthesized. The thiosemicarbazone in the latter two complexes behaves in a dianionic N,N,S-tridentate fashion. The platinum complex was found to have significant cytotoxicity toward four cancer cells lines, namely MDA-MB-231, MCF-7, HT-29, and HCT-116 but not toward the normal liver WRL-68 cell line. The apoptosis-inducing properties of the Pt complex was explored through fluorescence microscopy visualization, DNA fragmentation analysis and propidium iodide flow cytometry.
  4. Fulltext Optimal Training Configurations of a CNN-LSTM-Based Tracker for a Fall Frame Detection System
    Mohamed NA, Zulkifley MA, Ibrahim AA, Aouache M
    Sensors (Basel), 2021 Sep 28;21(19).
    PMID: 34640803 DOI: 10.3390/s21196485
    In recent years, there has been an immense amount of research into fall event detection. Generally, a fall event is defined as a situation in which a person unintentionally drops down onto a lower surface. It is crucial to detect the occurrence of fall events as early as possible so that any severe fall consequences can be minimized. Nonetheless, a fall event is a sporadic incidence that occurs seldomly that is falsely detected due to a wide range of fall conditions and situations. Therefore, an automated fall frame detection system, which is referred to as the SmartConvFall is proposed to detect the exact fall frame in a video sequence. It is crucial to know the exact fall frame as it dictates the response time of the system to administer an early treatment to reduce the fall's negative consequences and related injuries. Henceforth, searching for the optimal training configurations is imperative to ensure the main goal of the SmartConvFall is achieved. The proposed SmartConvFall consists of two parts, which are object tracking and instantaneous fall frame detection modules that rely on deep learning representations. The first stage will track the object of interest using a fully convolutional neural network (CNN) tracker. Various training configurations such as optimizer, learning rate, mini-batch size, number of training samples, and region of interest are individually evaluated to determine the best configuration to produce the best tracker model. Meanwhile, the second module goal is to determine the exact instantaneous fall frame by modeling the continuous object trajectories using the Long Short-Term Memory (LSTM) network. Similarly, the LSTM model will undergo various training configurations that cover different types of features selection and the number of stacked layers. The exact instantaneous fall frame is determined using an assumption that a large movement difference with respect to the ground level along the vertical axis can be observed if a fall incident happened. The proposed SmartConvFall is a novel technique as most of the existing methods still relying on detection rather than the tracking module. The SmartConvFall outperforms the state-of-the-art trackers, namely TCNN and MDNET-N trackers, with the highest expected average overlap, robustness, and reliability metrics of 0.1619, 0.6323, and 0.7958, respectively. The SmartConvFall also managed to produce the lowest number of tracking failures with only 43 occasions. Moreover, a three-stack LSTM delivers the lowest mean error with approximately one second delay time in locating the exact instantaneous fall frame. Therefore, the proposed SmartConvFall has demonstrated its potential and suitability to be implemented for a real-time application that could help to avoid any crucial fall consequences such as death and internal bleeding if the early treatment can be administered.
  5. Fulltext The Determinants of Undiagnosed Hypertension among Urban Community of Kuala Lumpur, Malaysia
    Ibrahim AA, Manaf MRA, Ismail NH
    Iran J Public Health, 2022 Jun;51(6):1323-1330.
    PMID: 36447985 DOI: 10.18502/ijph.v51i6.9677
    BACKGROUND: The prevalence of undiagnosed hypertension in Malaysia is 17.2%, which is higher compared to the known case of hypertension (13.1%) reported in 2015. For every two people diagnosed with hypertension, there will be three persons with undiagnosed hypertension; the trend has not changed since 2011. This study aimed to determine the determinants of undiagnosed hypertension among urban community of Kuala Lumpur, Malaysia.

    METHODS: This was a cross-sectional study conducted among 206 participants in Kuala Lumpur, Malaysia from the ongoing Prospective Urban Rural Epidemiology (PURE) project. The samples with complete variable data were taken from the second year of follow-up, starting Jan 2014 till Dec 2015, through convenience sampling. Data were analyzed using descriptive analysis, simple logistic regression, and multivariable logistic regression.

    RESULTS: Multivariable logistic regression showed that only four determinants were associated with undiagnosed hypertension which were the age group of 35 to 49 yr old (aOR: 5.9, 95% CI: 1.8; 19.1), secondary education level (aOR: 2.3, 95% CI: 1.1; 4.6), normal BMI (aOR: 5.1, 95% CI: 1.5; 16.6), and non-diabetes mellitus (aOR: 5.5, 95% CI: 2.5; 12.0).

    CONCLUSION: The determinants of undiagnosed hypertension in this study showed that low-risk groups of hypertension were highly underdiagnosed. The low-risk group of hypertension was easily approached at their working place. Thus, routine health screening and awareness campaigns should be emphasized substantially at the working place to detect undiagnosed hypertension. Early detection will be beneficial as early management can be initiated to prevent further complications.

  6. Fulltext Human Leukocyte Antigen (HLA) class I and II datasets for sudanese
    Dafalla AM, Edinur HA, Abdelwahed M, Elemam AA, Ibrahim AA, Mohamadani A, et al.
    Data Brief, 2019 Jun;24:104027.
    PMID: 31193964 DOI: 10.1016/j.dib.2019.104027
    Sudan is located in the heart of Africa and surrounded by eight countries with people of different ethnic origins. Historical records show that the population of the Sudan is a mixture of Arabic, West Asian Arabic and sub-Saharan African elements. The present survey provides data on allele lineages, and haplotype frequencies of Human Leukocyte Antigen (HLA) class I (HLA-A and HLA-B) and class II (HLA-DR and -HLA-DQ) loci in 11 Sudanese populations. The sampled individuals are all local transplant donors who provided informed consent for HLA analyses on their blood samples and were registered at National Cancer Institute, University of Gezira, Wad Medani. The HLA class I and II data reported here can be subjected for future analyses of genetic structure and health in Sudan. These include as reference datasets for identifying the association between HLA and diseases and for designing donor recruitment strategies.
  7. Fulltext Automated Glaucoma Screening and Diagnosis Based on Retinal Fundus Images Using Deep Learning Approaches: A Comprehensive Review
    Zedan MJM, Zulkifley MA, Ibrahim AA, Moubark AM, Kamari NAM, Abdani SR
    Diagnostics (Basel), 2023 Jun 26;13(13).
    PMID: 37443574 DOI: 10.3390/diagnostics13132180
    Glaucoma is a chronic eye disease that may lead to permanent vision loss if it is not diagnosed and treated at an early stage. The disease originates from an irregular behavior in the drainage flow of the eye that eventually leads to an increase in intraocular pressure, which in the severe stage of the disease deteriorates the optic nerve head and leads to vision loss. Medical follow-ups to observe the retinal area are needed periodically by ophthalmologists, who require an extensive degree of skill and experience to interpret the results appropriately. To improve on this issue, algorithms based on deep learning techniques have been designed to screen and diagnose glaucoma based on retinal fundus image input and to analyze images of the optic nerve and retinal structures. Therefore, the objective of this paper is to provide a systematic analysis of 52 state-of-the-art relevant studies on the screening and diagnosis of glaucoma, which include a particular dataset used in the development of the algorithms, performance metrics, and modalities employed in each article. Furthermore, this review analyzes and evaluates the used methods and compares their strengths and weaknesses in an organized manner. It also explored a wide range of diagnostic procedures, such as image pre-processing, localization, classification, and segmentation. In conclusion, automated glaucoma diagnosis has shown considerable promise when deep learning algorithms are applied. Such algorithms could increase the accuracy and efficiency of glaucoma diagnosis in a better and faster manner.
  8. Fulltext Intelligent Bone Age Assessment: An Automated System to Detect a Bone Growth Problem Using Convolutional Neural Networks with Attention Mechanism
    Zulkifley MA, Mohamed NA, Abdani SR, Kamari NAM, Moubark AM, Ibrahim AA
    Diagnostics (Basel), 2021 Apr 24;11(5).
    PMID: 33923215 DOI: 10.3390/diagnostics11050765
    Skeletal bone age assessment using X-ray images is a standard clinical procedure to detect any anomaly in bone growth among kids and babies. The assessed bone age indicates the actual level of growth, whereby a large discrepancy between the assessed and chronological age might point to a growth disorder. Hence, skeletal bone age assessment is used to screen the possibility of growth abnormalities, genetic problems, and endocrine disorders. Usually, the manual screening is assessed through X-ray images of the non-dominant hand using the Greulich-Pyle (GP) or Tanner-Whitehouse (TW) approach. The GP uses a standard hand atlas, which will be the reference point to predict the bone age of a patient, while the TW uses a scoring mechanism to assess the bone age using several regions of interest information. However, both approaches are heavily dependent on individual domain knowledge and expertise, which is prone to high bias in inter and intra-observer results. Hence, an automated bone age assessment system, which is referred to as Attention-Xception Network (AXNet) is proposed to automatically predict the bone age accurately. The proposed AXNet consists of two parts, which are image normalization and bone age regression modules. The image normalization module will transform each X-ray image into a standardized form so that the regressor network can be trained using better input images. This module will first extract the hand region from the background, which is then rotated to an upright position using the angle calculated from the four key-points of interest. Then, the masked and rotated hand image will be aligned such that it will be positioned in the middle of the image. Both of the masked and rotated images will be obtained through existing state-of-the-art deep learning methods. The last module will then predict the bone age through the Attention-Xception network that incorporates multiple layers of spatial-attention mechanism to emphasize the important features for more accurate bone age prediction. From the experimental results, the proposed AXNet achieves the lowest mean absolute error and mean squared error of 7.699 months and 108.869 months2, respectively. Therefore, the proposed AXNet has demonstrated its potential for practical clinical use with an error of less than one year to assist the experts or radiologists in evaluating the bone age objectively.
  9. Synthesis of porous 2D layered nickel oxide-reduced graphene oxide (NiO-rGO) hybrid composite for the efficient electrochemical detection of epinephrine in biological fluid
    Ramu AG, Umar A, Ibrahim AA, Algadi H, Ibrahim YSA, Wang Y, et al.
    Environ Res, 2021 09;200:111366.
    PMID: 34029547 DOI: 10.1016/j.envres.2021.111366
    In the present research work, 2D-Porous NiO decorated graphene nanocomposite was synthesized by hydrothermal method to monitored the concentration of epinephrine (EPI). The morphology (SEM and TEM) results confirmed 2D-Porous NiO nanoparticles firmly attached over graphene nanosheets. FTIR and XPS analysis confirmed the formation of nickel oxide formation and complete reduction of GO to rGO. The electrochemical activity of the proposed NiO-rGO/GCE modified electrode on epinephrine was analyzed by simple cyclic voltammetry technique. The proposed low cost NiO-rGO/GCE modified electrode showed excellent catalytic activity over GCE and rGO/GCE electrodes. Due to its high conductivity and charge transfer ability of the NiO-rGO/GCE modified electrode exhibited high sensitivity of EPI at optimized conditions. The anodic peak current of the EPI linearly increases with increasing the concertation of EPI. A wide linear range (50 μM-1000 μM) was achieved with high correlation coefficient (R2 = 0.9986) and the limit of detection (LOD) of NiO-rGO/GCE modified electrode was calculated to be 10 μM. NiO-rGO/GCE electrode showed good stability and repeatability towards the EPI oxidation. Mainly, the proposed NiO-rGO/GCE modified electrode showed good sensitivity of EPI in the human biological fluid with high recovery percentage. The low cost, NiO-rGO/GCE electrode could be the promising sensor electrode for the detection of Epinephrine in the real samples.
  10. Artificial Neural Networks to Solve the Singular Model with Neumann-Robin, Dirichlet and Neumann Boundary Conditions
    Nisar K, Sabir Z, Asif Zahoor Raja M, Ag Ibrahim AA, J P C Rodrigues J, Refahy Mahmoud S, et al.
    Sensors (Basel), 2021 Sep 29;21(19).
    PMID: 34640818 DOI: 10.3390/s21196498
    The aim of this work is to solve the case study singular model involving the Neumann-Robin, Dirichlet, and Neumann boundary conditions using a novel computing framework that is based on the artificial neural network (ANN), global search genetic algorithm (GA), and local search sequential quadratic programming method (SQPM), i.e., ANN-GA-SQPM. The inspiration to present this numerical framework comes through the objective of introducing a reliable structure that associates the operative ANNs features using the optimization procedures of soft computing to deal with such stimulating systems. Four different problems that are based on the singular equations involving Neumann-Robin, Dirichlet, and Neumann boundary conditions have been occupied to scrutinize the robustness, stability, and proficiency of the designed ANN-GA-SQPM. The proposed results through ANN-GA-SQPM have been compared with the exact results to check the efficiency of the scheme through the statistical performances for taking fifty independent trials. Moreover, the study of the neuron analysis based on three and 15 neurons is also performed to check the authenticity of the proposed ANN-GA-SQPM.
  11. Fulltext The role of electronic medical records in improving health care quality: A quasi-experimental study
    Ibrahim AA, Ahmad Zamzuri M'I, Ismail R, Ariffin AH, Ismail A, Muhamad Hasani MH, et al.
    Medicine (Baltimore), 2022 Jul 29;101(30):e29627.
    PMID: 35905245 DOI: 10.1097/MD.0000000000029627
    The Teleprimary Care-Oral Health Clinical Information System (TPC-OHCIS) is an updated electronic medical record (EMR) that has been applied in Malaysian primary healthcare. Recognizing the level of patient satisfaction following EMR implementation is crucial for assessing the performance of health care services. Hence, the main objective of this study was to compare the level of patient satisfaction between EMR-based clinics and paper-based clinics. The study was a quasi-experimental design that used a control group and was conducted among patients in 14 public primary healthcare facilities in the Seremban district of Malaysia from May 10, to June 30, 2021. Patient satisfaction was assessed using the validated Short-Form Patient Satisfaction Questionnaire, which consisted of 7 subscales. All data were analyzed using the IBM Statistical Package for Social Sciences version 21. A total of 321 patients consented to participate in this study, and 48.9% of them were from EMR clinics. The mean score for the communication subscale was the highest at 4.08 and 3.96 at EMR-adopted clinics and paper-based record clinics. There were significant differences in general satisfaction and communication subscales, with higher patient satisfaction found in clinics using EMR. With the utilization of EMR, patient satisfaction and communication in delivering healthcare services have improved.
  12. Fulltext Prevalence, reasons, and determinants of dietary supplements use among undergraduate female students of health and non-health colleges in a Saudi public university
    Islam MA, Al-Karasneh AF, Rizvi M, Nisa ZU, Albakheet AM, Alshagawi MA, et al.
    PLoS One, 2021;16(3):e0247295.
    PMID: 33657129 DOI: 10.1371/journal.pone.0247295
    PURPOSE: The aim of this study was to gather data from female students studying in both health and non-health colleges at Imam Abdulrahman Bin Faisal University and report the prevalence, reasons, and determinants of dietary supplements use.

    METHODS: A month-long cross-sectional study was conducted in health and non-health colleges affiliated to Imam Abdulrahman Bin Faisal University in Dammam, Saudi Arabia. Convenient sampling was employed, and the data was gathered through an online survey using the English and Arabic versions of the Dietary Supplement Questionnaire (DSQ). The data was analyzed using SPSS version 23 and Medcalc. The study was approved by an ethics committee.

    RESULTS: Data from 545 participants was collected. The overall prevalence of dietary supplement use was 32.7% (95% CI: 29.06%- 36.51%). The prevalence was 29.77% (95% CI: 25.29%- 34.56%) among students at all health colleges combined and, it was 37.50% (95% CI: 31.36%- 43.96%) among students at all non-health colleges. Most students used a brand product, spent a monthly cost of SAR 286 (USD 76.3) on supplements and agreed that supplements were good for health (N = 392, 71.9%). Students from non-health- colleges agreed that dietary supplements are good for health in greater numbers as compared to non-health college students (p < 0.001). Students aged ≥ 20 years, studying in a non-health college and up to 3rd year of study, were more 2 times more likely to agree that dietary supplements are good for health.

    CONCLUSION: Supplements were commonly used among female students at this university however, it was quite low as compared to students from other local and regional universities. Prevalence was higher in non-health colleges as compared to health colleges and the most commonly used supplements were brand products and, multivitamins, used for general health and well-being. This highlights the inclination of students towards supplement use.

  13. Status of vancomycin-resistant Enterococcus in species of wild birds: A systematic review and meta-analysis
    Wada Y, Ibrahim AB, Umar YA, Afolabi HA, Wada M, Alissa M, et al.
    J Infect Public Health, 2024 Apr 10;17(6):1023-1036.
    PMID: 38657438 DOI: 10.1016/j.jiph.2024.04.004
    Wild birds could be a reservoir of medically relevant microorganisms, particularly multidrug-resistant Enterococcus spp. Resistant bacteria's epidemiology and transmission between animals and humans has grown, and their zoonotic potential cannot be ignored. This is the first study to evaluate the status of vancomycin resistant enterococci (VRE) in various wild bird species using meta-analysis and a systematic review. In this study, the pooled prevalence was obtained by analyzing data from published articles on the occurrence of VRE in wild bird species. It's unclear how the antibiotic resistance gene transfer cycle affects wild birds. Google Scholar and PubMed were used to conduct the research. The data and study methodology was assessed and extracted by two reviewers independently, with a third reviewing the results. Heterogeneity between study and publication bias were analyzed using the random effect model. Thirty-eight studies were included in the meta-analysis. 382 out of the 4144 isolates tested, were VRE. The pooled prevalence of VRE among wild birds was estimated at 11.0% (95% CI; 6.9 -17.2%; I2 = 93.204%; P 
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