Displaying publications 81 - 100 of 1461 in total

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  1. Al-Hiyali MI, Yahya N, Faye I, Hussein AF
    Sensors (Basel), 2021 Aug 04;21(16).
    PMID: 34450699 DOI: 10.3390/s21165256
    The functional connectivity (FC) patterns of resting-state functional magnetic resonance imaging (rs-fMRI) play an essential role in the development of autism spectrum disorders (ASD) classification models. There are available methods in literature that have used FC patterns as inputs for binary classification models, but the results barely reach an accuracy of 80%. Additionally, the generalizability across multiple sites of the models has not been investigated. Due to the lack of ASD subtypes identification model, the multi-class classification is proposed in the present study. This study aims to develop automated identification of autism spectrum disorder (ASD) subtypes using convolutional neural networks (CNN) using dynamic FC as its inputs. The rs-fMRI dataset used in this study consists of 144 individuals from 8 independent sites, labeled based on three ASD subtypes, namely autistic disorder (ASD), Asperger's disorder (APD), and pervasive developmental disorder not otherwise specified (PDD-NOS). The blood-oxygen-level-dependent (BOLD) signals from 116 brain nodes of automated anatomical labeling (AAL) atlas are used, where the top-ranked node is determined based on one-way analysis of variance (ANOVA) of the power spectral density (PSD) values. Based on the statistical analysis of the PSD values of 3-level ASD and normal control (NC), putamen_R is obtained as the top-ranked node and used for the wavelet coherence computation. With good resolution in time and frequency domain, scalograms of wavelet coherence between the top-ranked node and the rest of the nodes are used as dynamic FC feature input to the convolutional neural networks (CNN). The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. Results of binary classification (ASD vs. NC) and multi-class classification (ASD vs. APD vs. PDD-NOS vs. NC) yielded, respectively, 89.8% accuracy and 82.1% macro-average accuracy, respectively. Findings from this study have illustrated the good potential of wavelet coherence technique in representing dynamic FC between brain nodes and open possibilities for its application in computer aided diagnosis of other neuropsychiatric disorders, such as depression or schizophrenia.
    Matched MeSH terms: Brain Mapping
  2. Al-Kadi MI, Reaz MB, Ali MA, Liu CY
    Sensors (Basel), 2014;14(7):13046-69.
    PMID: 25051031 DOI: 10.3390/s140713046
    This paper presents a comparison between the electroencephalogram (EEG) channels during scoliosis correction surgeries. Surgeons use many hand tools and electronic devices that directly affect the EEG channels. These noises do not affect the EEG channels uniformly. This research provides a complete system to find the least affected channel by the noise. The presented system consists of five stages: filtering, wavelet decomposing (Level 4), processing the signal bands using four different criteria (mean, energy, entropy and standard deviation), finding the useful channel according to the criteria's value and, finally, generating a combinational signal from Channels 1 and 2. Experimentally, two channels of EEG data were recorded from six patients who underwent scoliosis correction surgeries in the Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM) (the Medical center of National University of Malaysia). The combinational signal was tested by power spectral density, cross-correlation function and wavelet coherence. The experimental results show that the system-outputted EEG signals are neatly switched without any substantial changes in the consistency of EEG components. This paper provides an efficient procedure for analyzing EEG signals in order to avoid averaging the channels that lead to redistribution of the noise on both channels, reducing the dimensionality of the EEG features and preparing the best EEG stream for the classification and monitoring stage.
    Matched MeSH terms: Brain/surgery
  3. Al-Marri F, Reza F, Begum T, Hitam WHW, Jin GK, Xiang J
    J Integr Neurosci, 2018 Aug 15;17(3):257-269.
    PMID: 30338955 DOI: 10.31083/JIN-170058
    Visual cognitive function is important in the construction of executive function in daily life. Perception of visual number form (e.g. Arabic digits) and numerosity (numeric magnitude) is of interest to cognitive neuroscientists. Neural correlates and the functional measurement of number representations are complex events when their semantic categories are assimilated together with concepts of shape and color. Color perception can be processed further to modulate visual cognition. The Ishihara pseudoisochromatic plates are one of the best and most common screening tools for basic red-green color vision testing. However, there has been little study of visual cognitive function assessment using such pseudoisochromatic plates. 25 healthy normal trichromat volunteers were recruited and studied using a 128-sensor net to record event-related electroencephalogram. Subjects were asked to respond by pressing numbered buttons when they saw the number and non-number plates of the Ishihara color vision test. Amplitudes and latencies of N100 and P300 event related potential components were analyzed from 19 electrode sites in the international 10-20 system. A brain topographic map, cortical activation patterns, and Granger causation (effective connectivity) were analyzed from 128 electrode sites. No significant differences between N100 event related potential components for either stimulus indicates early selective attention processing was similar for number and non-number plate stimuli, but non-number plate stimuli evoked significantly higher amplitudes, longer latencies of the P300 event related potential component with a slower reaction time compared to number plate stimuli imply the allocation of attentional load was more in non-number plate processing. A different pattern of the asymmetric scalp voltage map was noticed for P300 components with a higher intensity in the left hemisphere for number plate tasks and higher intensity in the right hemisphere for non-number plate tasks. Asymmetric cortical activation and connectivity patterns revealed that number recognition occurred in the occipital and left frontal areas where as the consequence was limited to the occipital area during the non-number plate processing. Finally, results demonstrated that the visual recognition of numbers dissociates from the recognition of non-numbers at the level of defined neural networks. Number recognition was not only a process of visual perception and attention, but was also related to a higher level of cognitive function, that of language.
    Matched MeSH terms: Brain
  4. Al-Nema MY, Gaurav A
    Curr Top Med Chem, 2020;20(26):2404-2421.
    PMID: 32533817 DOI: 10.2174/1568026620666200613202641
    Schizophrenia is a severe mental disorder that affects more than 1% of the population worldwide. Dopamine system dysfunction and alterations in glutamatergic neurotransmission are strongly implicated in the aetiology of schizophrenia. To date, antipsychotic drugs are the only available treatment for the symptoms of schizophrenia. These medications, which act as D2-receptor antagonist, adequately address the positive symptoms of the disease, but they fail to improve the negative symptoms and cognitive impairment. In schizophrenia, cognitive impairment is a core feature of the disorder. Therefore, the treatment of cognitive impairment and the other symptoms related to schizophrenia remains a significant unmet medical need. Currently, phosphodiesterases (PDEs) are considered the best drug target for the treatment of schizophrenia since many PDE subfamilies are abundant in the brain regions that are relevant to cognition. Thus, this review aims to illustrate the mechanism of PDEs in treating the symptoms of schizophrenia and summarises the encouraging results of PDE inhibitors as anti-schizophrenic drugs in preclinical and clinical studies.
    Matched MeSH terms: Brain
  5. Al-Obaidi MMJ, Bahadoran A, Har LS, Mui WS, Rajarajeswaran J, Zandi K, et al.
    Virus Res, 2017 04 02;233:17-28.
    PMID: 28279803 DOI: 10.1016/j.virusres.2017.02.012
    Japanese encephalitis (JE) is a neurotropic flavivirus that causes inflammation in central nervous system (CNS), neuronal death and also compromises the structural and functional integrity of the blood-brain barrier (BBB). The aim of this study was to evaluate the BBB disruption and apoptotic process in Japanese encephalitis virus (JEV)-infected transfected human brain microvascular endothelial cells (THBMECs). THBMECs were overlaid by JEV with different MOIs (0.5, 1.0, 5.0 and 10.0) and monitored by electrical cell-substrate impedance sensing (ECIS) in a real-time manner in order to observe the barrier function of THBMECs. Additionally, the level of 43 apoptotic proteins was quantified in the virally infected cells with different MOIs at 24h post infection. Infection of THBMEC with JEV induced an acute reduction in transendothelial electrical resistance (TEER) after viral infection. Also, significant up-regulation of Bax, BID, Fas and Fasl and down-regulation of IGFBP-2, BID, p27 and p53 were observed in JEV infected THBMECs with 0.5 and 10 MOIs compared to uninfected cells. Hence, the permeability of THBMECs is compromised during the JEV infection. In addition high viral load of the virus has the potential to subvert the host cell apoptosis to optimize the course of viral infection through deactivation of pro-apoptotic proteins.
    Matched MeSH terms: Blood-Brain Barrier/metabolism*; Blood-Brain Barrier/virology; Brain/blood supply; Brain/metabolism; Brain/virology
  6. Al-Obaidi MMJ, Desa MNM
    Cell Mol Neurobiol, 2018 Oct;38(7):1349-1368.
    PMID: 30117097 DOI: 10.1007/s10571-018-0609-2
    This review aims to elucidate the different mechanisms of blood brain barrier (BBB) disruption that may occur due to invasion by different types of bacteria, as well as to show the bacteria-host interactions that assist the bacterial pathogen in invading the brain. For example, platelet-activating factor receptor (PAFR) is responsible for brain invasion during the adhesion of pneumococci to brain endothelial cells, which might lead to brain invasion. Additionally, the major adhesin of the pneumococcal pilus-1, RrgA is able to bind the BBB endothelial receptors: polymeric immunoglobulin receptor (pIgR) and platelet endothelial cell adhesion molecule (PECAM-1), thus leading to invasion of the brain. Moreover, Streptococcus pneumoniae choline binding protein A (CbpA) targets the common carboxy-terminal domain of the laminin receptor (LR) establishing initial contact with brain endothelium that might result in BBB invasion. Furthermore, BBB disruption may occur by S. pneumoniae penetration through increasing in pro-inflammatory markers and endothelial permeability. In contrast, adhesion, invasion, and translocation through or between endothelial cells can be done by S. pneumoniae without any disruption to the vascular endothelium, upon BBB penetration. Internalins (InlA and InlB) of Listeria monocytogenes interact with its cellular receptors E-cadherin and mesenchymal-epithelial transition (MET) to facilitate invading the brain. L. monocytogenes species activate NF-κB in endothelial cells, encouraging the expression of P- and E-selectin, intercellular adhesion molecule 1 (ICAM-1), and Vascular cell adhesion protein 1 (VCAM-1), as well as IL-6 and IL-8 and monocyte chemoattractant protein-1 (MCP-1), all these markers assist in BBB disruption. Bacillus anthracis species interrupt both adherens junctions (AJs) and tight junctions (TJs), leading to BBB disruption. Brain microvascular endothelial cells (BMECs) permeability and BBB disruption are induced via interendothelial junction proteins reduction as well as up-regulation of IL-1α, IL-1β, IL-6, TNF-α, MCP-1, macrophage inflammatory proteins-1 alpha (MIP1α) markers in Staphylococcus aureus species. Streptococcus agalactiae or Group B Streptococcus toxins (GBS) enhance IL-8 and ICAM-1 as well as nitric oxide (NO) production from endothelial cells via the expression of inducible nitric oxide synthase (iNOS) enhancement, resulting in BBB disruption. While Gram-negative bacteria, Haemophilus influenza OmpP2 is able to target the common carboxy-terminal domain of LR to start initial interaction with brain endothelium, then invade the brain. H. influenza type b (HiB), can induce BBB permeability through TJ disruption. LR and PAFR binding sites have been recognized as common routes of CNS entrance by Neisseria meningitidis. N. meningitidis species also initiate binding to BMECs and induces AJs deformation, as well as inducing specific cleavage of the TJ component occludin through the release of host MMP-8. Escherichia coli bind to BMECs through LR, resulting in IL-6 and IL-8 release and iNOS production, as well as resulting in disassembly of TJs between endothelial cells, facilitating BBB disruption. Therefore, obtaining knowledge of BBB disruption by different types of bacterial species will provide a picture of how the bacteria enter the central nervous system (CNS) which might support the discovery of therapeutic strategies for each bacteria to control and manage infection.
    Matched MeSH terms: Blood-Brain Barrier/metabolism*; Blood-Brain Barrier/microbiology*; Brain/metabolism*; Brain/microbiology*
  7. Al-Qaysi ZT, Zaidan BB, Zaidan AA, Suzani MS
    Comput Methods Programs Biomed, 2018 Oct;164:221-237.
    PMID: 29958722 DOI: 10.1016/j.cmpb.2018.06.012
    CONTEXT: Intelligent wheelchair technology has recently been utilised to address several mobility problems. Techniques based on brain-computer interface (BCI) are currently used to develop electric wheelchairs. Using human brain control in wheelchairs for people with disability has elicited widespread attention due to its flexibility.

    OBJECTIVE: This study aims to determine the background of recent studies on wheelchair control based on BCI for disability and map the literature survey into a coherent taxonomy. The study intends to identify the most important aspects in this emerging field as an impetus for using BCI for disability in electric-powered wheelchair (EPW) control, which remains a challenge. The study also attempts to provide recommendations for solving other existing limitations and challenges.

    METHODS: We systematically searched all articles about EPW control based on BCI for disability in three popular databases: ScienceDirect, IEEE and Web of Science. These databases contain numerous articles that considerably influenced this field and cover most of the relevant theoretical and technical issues.

    RESULTS: We selected 100 articles on the basis of our inclusion and exclusion criteria. A large set of articles (55) discussed on developing real-time wheelchair control systems based on BCI for disability signals. Another set of articles (25) focused on analysing BCI for disability signals for wheelchair control. The third set of articles (14) considered the simulation of wheelchair control based on BCI for disability signals. Four articles designed a framework for wheelchair control based on BCI for disability signals. Finally, one article reviewed concerns regarding wheelchair control based on BCI for disability signals.

    DISCUSSION: Since 2007, researchers have pursued the possibility of using BCI for disability in EPW control through different approaches. Regardless of type, articles have focused on addressing limitations that impede the full efficiency of BCI for disability and recommended solutions for these limitations.

    CONCLUSIONS: Studies on wheelchair control based on BCI for disability considerably influence society due to the large number of people with disability. Therefore, we aim to provide researchers and developers with a clear understanding of this platform and highlight the challenges and gaps in the current and future studies.

    Matched MeSH terms: Brain-Computer Interfaces*
  8. Al-Qazzaz NK, Bin Mohd Ali SH, Ahmad SA, Islam MS, Escudero J
    Sensors (Basel), 2015;15(11):29015-35.
    PMID: 26593918 DOI: 10.3390/s151129015
    We performed a comparative study to select the efficient mother wavelet (MWT) basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during a working memory (WM) task recorded through electro-encephalography (EEG). Nineteen EEG electrodes were placed on the scalp following the 10-20 system. These electrodes were then grouped into five recording regions corresponding to the scalp area of the cerebral cortex. Sixty-second WM task data were recorded from ten control subjects. Forty-five MWT basis functions from orthogonal families were investigated. These functions included Daubechies (db1-db20), Symlets (sym1-sym20), and Coiflets (coif1-coif5). Using ANOVA, we determined the MWT basis functions with the most significant differences in the ability of the five scalp regions to maximize their cross-correlation with the EEG signals. The best results were obtained using "sym9" across the five scalp regions. Therefore, the most compatible MWT with the EEG signals should be selected to achieve wavelet denoising, decomposition, reconstruction, and sub-band feature extraction. This study provides a reference of the selection of efficient MWT basis functions.
    Matched MeSH terms: Brain
  9. Al-Qazzaz NK, Ali SH, Ahmad SA, Islam S
    Neuropsychiatr Dis Treat, 2014;10:1743-51.
    PMID: 25246795 DOI: 10.2147/NDT.S68443
    The early detection of poststroke dementia (PSD) is important for medical practitioners to customize patient treatment programs based on cognitive consequences and disease severity progression. The aim is to diagnose and detect brain degenerative disorders as early as possible to help stroke survivors obtain early treatment benefits before significant mental impairment occurs. Neuropsychological assessments are widely used to assess cognitive decline following a stroke diagnosis. This study reviews the function of the available neuropsychological assessments in the early detection of PSD, particularly vascular dementia (VaD). The review starts from cognitive impairment and dementia prevalence, followed by PSD types and the cognitive spectrum. Finally, the most usable neuropsychological assessments to detect VaD were identified. This study was performed through a PubMed and ScienceDirect database search spanning the last 10 years with the following keywords: "post-stroke"; "dementia"; "neuro-psychological"; and "assessments". This study focuses on assessing VaD patients on the basis of their stroke risk factors and cognitive function within the first 3 months after stroke onset. The search strategy yielded 535 articles. After application of inclusion and exclusion criteria, only five articles were considered. A manual search was performed and yielded 14 articles. Twelve articles were included in the study design and seven articles were associated with early dementia detection. This review may provide a means to identify the role of neuropsychological assessments as early PSD detection tests.
    Matched MeSH terms: Brain
  10. Al-Qazzaz NK, Ali SH, Ahmad SA, Islam S, Mohamad K
    Neuropsychiatr Dis Treat, 2014;10:1677-91.
    PMID: 25228808 DOI: 10.2147/NDT.S67184
    Cognitive impairment and memory dysfunction following stroke diagnosis are common symptoms that significantly affect the survivors' quality of life. Stroke patients have a high potential to develop dementia within the first year of stroke onset. Currently, efforts are being exerted to assess stroke effects on the brain, particularly in the early stages. Numerous neuropsychological assessments are being used to evaluate and differentiate cognitive impairment and dementia following stroke. This article focuses on the role of available neuropsychological assessments in detection of dementia and memory loss after stroke. This review starts with stroke types and risk factors associated with dementia development, followed by a brief description of stroke diagnosis criteria and the effects of stroke on the brain that lead to cognitive impairment and end with memory loss. This review aims to combine available neuropsychological assessments to develop a post-stroke memory assessment (PSMA) scheme based on the most recognized and available studies. The proposed PSMA is expected to assess different types of memory functionalities that are related to different parts of the brain according to stroke location. An optimal therapeutic program that would help stroke patients enjoy additional years with higher quality of life is presented.
    Matched MeSH terms: Brain
  11. Al-Qazzaz NK, Hamid Bin Mohd Ali S, Ahmad SA, Islam MS, Escudero J
    Sensors (Basel), 2017 Jun 08;17(6).
    PMID: 28594352 DOI: 10.3390/s17061326
    Characterizing dementia is a global challenge in supporting personalized health care. The electroencephalogram (EEG) is a promising tool to support the diagnosis and evaluation of abnormalities in the human brain. The EEG sensors record the brain activity directly with excellent time resolution. In this study, EEG sensor with 19 electrodes were used to test the background activities of the brains of five vascular dementia (VaD), 15 stroke-related patients with mild cognitive impairment (MCI), and 15 healthy subjects during a working memory (WM) task. The objective of this study is twofold. First, it aims to enhance the recorded EEG signals using a novel technique that combines automatic independent component analysis (AICA) and wavelet transform (WT), that is, the AICA-WT technique; second, it aims to extract and investigate the spectral features that characterize the post-stroke dementia patients compared to the control subjects. The proposed AICA-WT technique is a four-stage approach. In the first stage, the independent components (ICs) were estimated. In the second stage, three-step artifact identification metrics were applied to detect the artifactual components. The components identified as artifacts were marked as critical and denoised through DWT in the third stage. In the fourth stage, the corrected ICs were reconstructed to obtain artifact-free EEG signals. The performance of the proposed AICA-WT technique was compared with those of two other techniques based on AICA and WT denoising methods using cross-correlation X C o r r and peak signal to noise ratio ( P S N R ) (ANOVA, p ˂ 0.05). The AICA-WT technique exhibited the best artifact removal performance. The assumption that there would be a deceleration of EEG dominant frequencies in VaD and MCI patients compared with control subjects was assessed with AICA-WT (ANOVA, p ˂ 0.05). Therefore, this study may provide information on post-stroke dementia particularly VaD and stroke-related MCI patients through spectral analysis of EEG background activities that can help to provide useful diagnostic indexes by using EEG signal processing.
    Matched MeSH terms: Brain
  12. Al-Qazzaz NK, Alyasseri ZAA, Abdulkareem KH, Ali NS, Al-Mhiqani MN, Guger C
    Comput Biol Med, 2021 10;137:104799.
    PMID: 34478922 DOI: 10.1016/j.compbiomed.2021.104799
    Stroke is the second foremost cause of death worldwide and is one of the most common causes of disability. Several approaches have been proposed to manage stroke patient rehabilitation such as robotic devices and virtual reality systems, and researchers have found that the brain-computer interfaces (BCI) approaches can provide better results. Therefore, the most challenging tasks with BCI applications involve identifying the best technique(s) that can reveal the neuron stimulus information from the patients' brains and extracting the most effective features from these signals as well. Accordingly, the main novelty of this paper is twofold: propose a new feature fusion method for motor imagery (MI)-based BCI and develop an automatic MI framework to detect the changes pre- and post-rehabilitation. This study investigated the electroencephalography (EEG) dataset from post-stroke patients with upper extremity hemiparesis. All patients performed 25 MI-based BCI sessions with follow up assessment visits to examine the functional changes before and after EEG neurorehabilitation. In the first stage, conventional filters and automatic independent component analysis with wavelet transform (AICA-WT) denoising technique were used. Next, attributes from time, entropy and frequency domains were computed, and the effective features were combined into time-entropy-frequency (TEF) attributes. Consequently, the AICA-WT and the TEF fusion set were utilised to develop an AICA-WT-TEF framework. Then, support vector machine (SVM), k-nearest neighbours (kNN) and random forest (RF) classification technique were tested for MI-based BCI rehabilitation. The proposed AICA-WT-TEF framework with RF classifier achieves the best results compared with other classifiers. Finally, the proposed framework and feature fusion set achieve a significant performance in terms of accuracy measures compared to the state-of-the-art. Therefore, the proposed methods could be crucial for improving the process of automatic MI rehabilitation and are recommended for implementation in real-time applications.
    Matched MeSH terms: Brain-Computer Interfaces*
  13. Al-Quraishi MS, Elamvazuthi I, Tang TB, Al-Qurishi M, Adil SH, Ebrahim M
    Brain Sci, 2021 May 27;11(6).
    PMID: 34071982 DOI: 10.3390/brainsci11060713
    Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have temporal and spatial characteristics that may complement each other and, therefore, pose an intriguing approach for brain-computer interaction (BCI). In this work, the relationship between the hemodynamic response and brain oscillation activity was investigated using the concurrent recording of fNIRS and EEG during ankle joint movements. Twenty subjects participated in this experiment. The EEG was recorded using 20 electrodes and hemodynamic responses were recorded using 32 optodes positioned over the motor cortex areas. The event-related desynchronization (ERD) feature was extracted from the EEG signal in the alpha band (8-11) Hz, and the concentration change of the oxy-hemoglobin (oxyHb) was evaluated from the hemodynamics response. During the motor execution of the ankle joint movements, a decrease in the alpha (8-11) Hz amplitude (desynchronization) was found to be correlated with an increase of the oxyHb (r = -0.64061, p < 0.00001) observed on the Cz electrode and the average of the fNIRS channels (ch28, ch25, ch32, ch35) close to the foot area representation. Then, the correlated channels in both modalities were used for ankle joint movement classification. The result demonstrates that the integrated modality based on the correlated channels provides a substantial enhancement in ankle joint classification accuracy of 93.01 ± 5.60% (p < 0.01) compared with single modality. These results highlight the potential of the bimodal fNIR-EEG approach for the development of future BCI for lower limb rehabilitation.
    Matched MeSH terms: Brain-Computer Interfaces
  14. Al-Rahbi B, Zakaria R, Othman Z, Hassan A, Ahmad AH
    ScientificWorldJournal, 2014;2014:310821.
    PMID: 24550703 DOI: 10.1155/2014/310821
    A possible interaction between glucocorticoids and estrogen-induced increases in brain-derived-neurotrophic factor (BDNF) expression in enhancing depressive-like behaviour has been documented. Here we evaluated the effects of Tualang honey, a phytoestrogen, and 17 β -estradiol (E2) on the depressive-like behaviour, stress hormones, and BDNF concentration in stressed ovariectomised (OVX) rats. The animals were divided into six groups: (i) nonstressed sham-operated control, (ii) stressed sham-operated control, (iii) nonstressed OVX, (iv) stressed OVX, (v) stressed OVX treated with E2 (20  μg daily, sc), and (vi) stressed OVX treated with Tualang honey (0.2 g/kg body weight daily, orally). Two months after surgery, the animals were subjected to social instability stress procedure followed by forced swimming test. Struggling time, immobility time, and swimming time were scored. Serum adrenocorticotropic hormone (ACTH) and corticosterone levels, and the BDNF concentration were determined using commercially available ELISA kits. Stressed OVX rats displayed increased depressive-like behaviour with significantly increased serum ACTH and corticosterone levels, while the BDNF concentration was significantly decreased compared to other experimental groups. These changes were notably reversed by both E2 and Tualang honey. In conclusion, both Tualang honey and E2 mediate antidepressive-like effects in stressed OVX rats, possibly acting via restoration of hypothalamic-pituitary-adrenal axis and enhancement of the BDNF concentration.
    Matched MeSH terms: Brain-Derived Neurotrophic Factor/metabolism*
  15. Al-Talib H, Hasan H, Yean CY, Al-Ashwal SM, Ravichandran M
    Jpn J Infect Dis, 2011;64(1):58-60.
    PMID: 21266757
    Panton-Valentine leukocidin (PVL) is a cytotoxin which causes leukocyte destruction and tissue necrosis. Although it is produced by fewer than 5% of Staphylococcus aureus strains, PVL-producing S. aureus is emerging as a serious problem worldwide. There has been a marked increase in the incidence of necrotizing lung infections with a very high mortality associated with these strains. This report describes a fatal case of hospital-acquired necrotizing pneumonia caused by PVL-positive methicillin-susceptible S. aureus in a patient with a brain tumor.
    Matched MeSH terms: Brain Neoplasms/complications
  16. Alawi M, Lee PF, Deng ZD, Goh YK, Croarkin PE
    J Neural Eng, 2023 Mar 16;20(2).
    PMID: 36240726 DOI: 10.1088/1741-2552/ac9a76
    Objective. The therapeutic application of noninvasive brain stimulation modalities such as transcranial magnetic stimulation (TMS) has expanded in terms of indications and patient populations. Often neurodevelopmental and neurodegenerative changes are not considered in research studies and clinical applications. This study sought to examine TMS dosing across time points in the life cycle.Approach. TMS induced electric fields with a figure-of-eight coil was simulated at left dorsolateral prefrontal cortex regions and taken in vertex as a control region. Realistic magnetic resonance imaging-based head models (N= 48) were concurrently examined in a cross-sectional study of three different age groups (children, adults, and elderlies).Main results. Age had a negative correlation with electric field peaks in white matter, grey matter and cerebrospinal fluid (P< 0.001). Notably, the electric field map in children displayed the widest cortical surface spread of TMS induced electric fields.Significance. Age-related anatomical geometry beneath the coil stimulation site had a significant impact on the TMS induced electric fields for different age groups. Safety considerations for TMS applications and protocols in children are warranted based on the present electric field findings.
    Matched MeSH terms: Brain/physiology
  17. Albart SA, Yusof Khan AHK, Abdul Rashid A, Wan Zaidi WA, Bidin MZ, Looi I, et al.
    PeerJ, 2022;10:e13310.
    PMID: 35469195 DOI: 10.7717/peerj.13310
    BACKGROUND: Despite rapid advances in acute ischaemic stroke (AIS) management, many healthcare professionals (HCPs) might not be aware of the latest recommended management of AIS patients. Therefore, we aimed to determine the level and factors associated with AIS management knowledge among Malaysian HCPs.

    METHODS: This cross-sectional online questionnaire study was conducted nationwide among 627 HCPs in Malaysia using the Acute Stroke Management Questionnaire (ASMaQ). Multiple logistic regression was used to predict the relationship between the independent variables (age, gender, years of service, profession, work setting, work sector, seeing stroke patients in daily practice, and working with specialists) and the outcome variable (good vs poor knowledge).

    RESULTS: Approximately 76% (95% CI [73-79%]) of HCPs had good overall knowledge of stroke. The highest proportion of HCPs with good knowledge was noted for General Stroke Knowledge (GSK) [88.5% (95% CI [86-91%])], followed by Advanced Stroke Management (ASM) [61.2% (95% CI [57-65%])] and Hyperacute Stroke Management (HSM) [58.1% (95% CI [54-62%])]. The odds of having poor knowledge of stroke were significantly higher among non-doctor HCPs [adjusted OR = 3.46 (95% CI [1.49-8.03]), P = 0.004]; among those not seeing stroke patients in daily practice [adjusted OR = 2.67 (95% CI [1.73-4.10]), P < 0.001]; and among those working without specialists [adjusted OR = 2.41 (95% CI [1.38-4.18]), P = 0.002].

    CONCLUSIONS: Stroke education should be prioritised for HCPs with limited experience and guidance. All HCPs need to be up-to-date on the latest AIS management and be able to make a prompt referral to an appropriate facility. Therefore, more stroke patients will benefit from advanced stroke care.

    Matched MeSH terms: Brain Ischemia*
  18. Albart SA, Yusof Khan AHK, Wan Zaidi WA, Muthuppalaniappan AM, Kandavello G, Koh GT, et al.
    Med J Malaysia, 2023 May;78(3):389-403.
    PMID: 37271850
    INTRODUCTION: About 20 to 40% of ischaemic stroke causes are cryptogenic. Embolic stroke of undetermined source (ESUS) is a subtype of cryptogenic stroke which is diagnosed based on specific criteria. Even though patent foramen ovale (PFO) is linked with the risk of stroke, it is found in about 25% of the general population, so it might be an innocent bystander. The best way to treat ESUS patients with PFO is still up for discussion.

    MATERIALS AND METHODS: Therefore, based on current evidence and expert opinion, Malaysian expert panels from various disciplines have gathered to discuss the management of ESUS patients with PFO. This consensus sought to educate Malaysian healthcare professionals to diagnose and manage PFO in ESUS patients based on local resources and facilities.

    RESULTS: Based on consensus, the Malaysian expert recommended PFO closure for embolic stroke patients who were younger than 60, had high RoPE scores and did not require long-term anticoagulation. However, the decision should be made after other mechanisms of stroke have been ruled out via thorough investigation and multidisciplinary evaluation. The PFO screening should be made using readily available imaging modalities, ideally contrasttransthoracic echocardiogram (c-TTE) or contrasttranscranial Doppler (c-TCD). The contrast-transesophageal echocardiogram (c-TEE) should be used for the confirmation of PFO diagnosis. The experts advised closing PFO as early as possible because there is limited evidence for late closure. For the post-closure follow-up management, dual antiplatelet therapy (DAPT) for one to three months, followed by single antiplatelet therapy (APT) for six months, is advised. Nonetheless, with joint care from a cardiologist and a neurologist, the multidisciplinary team will decide on the continuation of therapy.

    Matched MeSH terms: Brain Ischemia*
  19. Albitar O, Harun SN, Abidin NE, Tangiisuran B, Zainal H, Looi I, et al.
    J Stroke Cerebrovasc Dis, 2020 Oct;29(10):105173.
    PMID: 32912507 DOI: 10.1016/j.jstrokecerebrovasdis.2020.105173
    BACKGROUND: Diabetes and obesity are established risk factors for stroke. The current study aimed to assess risk factors of ischemic stroke recurrence in diabetic patients based on their body mass index (BMI).

    METHODS: A total of 4005 diabetic patients who had a history of ischemic stroke were identified in a retrospective cross-sectional dataset from the Malaysian National Neurology Registry. Patients were classified based on BMI, and multivariable regression analysis was used to evaluate the association between risk factors and recurrent ischemic stroke.

    RESULTS: Among obese patients, those with ischemic heart disease (aOR, 1.873; 95% CI, 1.131-3.103), received formal education (aOR, 2.236; 95% CI, 1.306-3.830), and received anti-diabetic medication (aOR, 1.788; 95% CI, 1.180-2.708) had a higher stroke recurrence risk, while receiving angiotensin receptors blockers (aOR, 0.261; 95% CI, 0.126-0.543) lowered the odds of recurrence. Overweight patients with hypertension (aOR, 1.011; 95% CI, 1.002-1.019) for over 10 years (aOR, 3.385; 95% CI, 1.088-10.532) and diabetes prior to the first stroke (aOR, 1.823; 95% CI, 1.020-3.259) as well as those received formal education (aOR, 2.403; 95% CI, 1.126-5.129) had higher odds of stroke recurrence, while receiving angiotensin-converting enzyme inhibitors (aOR, 0.244; 95% CI, 0.111-0.538) lowered the recurrence risk. Normal weight East Malaysians (aOR, 0.351; 95% CI, 0.164-0.750) receiving beta-blockers (aOR, 0.410; 95% CI, 0.174-0.966) had lower odds of stroke recurrence.

    CONCLUSIONS: Ischemic heart disease, hypertension, receiving anti-hypertensive agents, and educational level were independent predictors of recurrent stroke in obese patients. Managing the modifiable risk factors can decrease the odds of stroke recurrence.

    Matched MeSH terms: Brain Ischemia
  20. Aldoghachi AF, Tor YS, Redzun SZ, Lokman KAB, Razaq NAA, Shahbudin AF, et al.
    PLoS One, 2019;14(1):e0211241.
    PMID: 30677092 DOI: 10.1371/journal.pone.0211241
    BACKGROUND: Brain-derived neurotrophic factor (BDNF) is a neurotrophin found in abundance in brain regions such as the hippocampus, cortex, cerebellum and basal forebrain. It has been associated with the risk of susceptibility to major depressive disorder (MDD). This study aimed to determine the association of three BDNF variants (rs6265, rs1048218 and rs1048220) with Malaysian MDD patients.

    METHODS: The correlation of these variants to the plasma BDNF level among Malaysian MDD patients was assessed. A total of 300 cases and 300 matched controls recruited from four public hospitals within the Klang Valley of Selangor State, Malaysia and matched for age, sex and ethnicity were screened for BDNF rs6265, rs1048218 and rs1048220 using high resolution melting (HRM).

    FINDINGS: BDNF rs1048218 and BDNF rs1048220 were monomorphic and were excluded from further analysis. The distribution of the alleles and genotypes for BDNF rs6265 was in Hardy-Weinberg equilibrium for the controls (p = 0.13) but was in Hardy Weinberg disequilibrium for the cases (p = 0.011). Findings from this study indicated that having BDNF rs6265 in the Malaysian population increase the odds of developing MDD by 2.05 folds (95% CI = 1.48-3.65). Plasma from 206 cases and 206 controls were randomly selected to measure the BDNF level using enzyme-linked immunosorbent assay (ELISA). A significant decrease in the plasma BDNF level of the cases as compared to controls (p<0.0001) was observed. However, there was no evidence of the effect of the rs6265 genotypes on the BDNF level indicating a possible role of other factors in modulating the BDNF level that warrants further investigation.

    CONCLUSION: The study indicated that having the BDNF rs6265 allele (A) increase the risk of developing MDD in the Malaysian population suggesting a possible role of BDNF in the etiology of the disorder.

    Matched MeSH terms: Brain-Derived Neurotrophic Factor/blood*; Brain-Derived Neurotrophic Factor/genetics*
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