Displaying publications 61 - 80 of 1462 in total

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  1. Jamil Al-Obaidi MM, Desa MNM
    J Neurosci Res, 2023 Nov;101(11):1687-1698.
    PMID: 37462109 DOI: 10.1002/jnr.25232
    Coronaviruses are prevalent in mammals and birds, including humans and bats, and they often spread through airborne droplets. In humans, these droplets then interact with angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2), which are the main receptors for the SARS-CoV-2 virus. It can infect several organs, including the brain. The blood-brain barrier (BBB) is designed to maintain the homeostatic neural microenvironment of the brain, which is necessary for healthy neuronal activity, function, and stability. It prevents viruses from entering the brain parenchyma and does not easily allow chemicals to pass into the brain while assisting numerous compounds in exiting the brain. The purpose of this review was to examine how COVID-19 influences the BBB along with the mechanisms that indicate the BBB's deterioration. In addition, the cellular mechanism through which SARS-CoV-2 causes BBB destruction by binding to ACE2 was evaluated and addressed. The mechanisms of the immunological reaction that occurs during COVID-19 infection that may contribute to the breakdown of the BBB were also reviewed. It was discovered that the integrity of the tight junction (TJs), basement membrane, and adhesion molecules was damaged during COVID-19 infection, which led to the breakdown of the BBB. Therefore, understanding how the BBB is disrupted by COVID-19 infection will provide an indication of how the SARS-CoV-2 virus is able to reach the central nervous system (CNS). The findings of this research may help in the identification of treatment options for COVID-19 that can control and manage the infection.
    Matched MeSH terms: Brain/metabolism
  2. Chua TH, Takano A
    Malays J Pathol, 2021 04;43(1):121-125.
    PMID: 33903314
    No abstract available.
    Matched MeSH terms: Brain
  3. Grover CS, Thiagarajah S
    Med J Malaysia, 2014 Dec;69(6):268-72.
    PMID: 25934957 MyJurnal
    Our objective was to study the profile of cerebrovascular accidents and proportion of cerebral haemorrhage (CH) among stroke patients. This project was designed after we observed higher incidence of CH in Miri hospital as compared to conventionally reported data.

    METHODS: This was a prospective observational study conducted from 1st June 2008 to 31st May 2009. All patients admitted in both male and female wards of the Medical Unit with the first incidence of a stroke were recruited for analysis. CT scan brain was done in all patients.

    RESULTS: Total admissions in one year in the medical department were 3204 patients, both male and female together, out of which 215 were due to a first incidence of stroke; Stroke accounted for 6.7% of admissions and 16.8% of deaths in medical unit. 139 (64.7%) were ischaemic strokes and 76 (35.3%) were cerebral haemorrhages. The incidence of CH (35.3%) was high compared to regional data. 71.7% (154) patients had preexisting hypertension. Higher incidence of hypertension, diabetes mellitus and aspirin intake was noted in the ischaemic group. Also compliance to treatment for hypertension was better in the Ischaemic group with more defaults in CH category (P<0.01). Significantly more deaths were noted in patients with higher systolic blood pressure on presentation, poor Glasgow Coma Scale (GCS) and those with dysphagia.

    CONCLUSION: Every third stroke was due to cerebral hemorrhage; CH patients were largely unaware of their hypertension or were altogether treatment naïve or defaulters while compliance was far better in ischaemic stroke category.
    Matched MeSH terms: Brain
  4. Zafar R, Kamel N, Naufal M, Malik AS, Dass SC, Ahmad RF, et al.
    Australas Phys Eng Sci Med, 2018 Sep;41(3):633-645.
    PMID: 29948968 DOI: 10.1007/s13246-018-0656-5
    Neuroscientists have investigated the functionality of the brain in detail and achieved remarkable results but this area still need further research. Functional magnetic resonance imaging (fMRI) is considered as the most reliable and accurate technique to decode the human brain activity, on the other hand electroencephalography (EEG) is a portable and low cost solution in brain research. The purpose of this study is to find whether EEG can be used to decode the brain activity patterns like fMRI. In fMRI, data from a very specific brain region is enough to decode the brain activity patterns due to the quality of data. On the other hand, EEG can measure the rapid changes in neuronal activity patterns due to its higher temporal resolution i.e., in msec. These rapid changes mostly occur in different brain regions. In this study, multivariate pattern analysis (MVPA) is used both for EEG and fMRI data analysis and the information is extracted from distributed activation patterns of the brain. The significant information among different classes is extracted using two sample t test in both data sets. Finally, the classification analysis is done using the support vector machine. A fair comparison of both data sets is done using the same analysis techniques, moreover simultaneously collected data of EEG and fMRI is used for this comparison. The final analysis is done with the data of eight participants; the average result of all conditions are found which is 65.7% for EEG data set and 64.1% for fMRI data set. It concludes that EEG is capable of doing brain decoding with the data from multiple brain regions. In other words, decoding accuracy with EEG MVPA is as good as fMRI MVPA and is above chance level.
    Matched MeSH terms: Brain/physiology*; Brain Mapping*
  5. Asaduzzaman K, Reaz MB, Mohd-Yasin F, Sim KS, Hussain MS
    Adv Exp Med Biol, 2010;680:593-9.
    PMID: 20865544 DOI: 10.1007/978-1-4419-5913-3_65
    Electroencephalogram (EEG) serves as an extremely valuable tool for clinicians and researchers to study the activity of the brain in a non-invasive manner. It has long been used for the diagnosis of various central nervous system disorders like seizures, epilepsy, and brain damage and for categorizing sleep stages in patients. The artifacts caused by various factors such as Electrooculogram (EOG), eye blink, and Electromyogram (EMG) in EEG signal increases the difficulty in analyzing them. Discrete wavelet transform has been applied in this research for removing noise from the EEG signal. The effectiveness of the noise removal is quantitatively measured using Root Mean Square (RMS) Difference. This paper reports on the effectiveness of wavelet transform applied to the EEG signal as a means of removing noise to retrieve important information related to both healthy and epileptic patients. Wavelet-based noise removal on the EEG signal of both healthy and epileptic subjects was performed using four discrete wavelet functions. With the appropriate choice of the wavelet function (WF), it is possible to remove noise effectively to analyze EEG significantly. Result of this study shows that WF Daubechies 8 (db8) provides the best noise removal from the raw EEG signal of healthy patients, while WF orthogonal Meyer does the same for epileptic patients. This algorithm is intended for FPGA implementation of portable biomedical equipments to detect different brain state in different circumstances.
    Matched MeSH terms: Brain/physiology; Brain/physiopathology
  6. Sakharkar MK, Kashmir Singh SK, Rajamanickam K, Mohamed Essa M, Yang J, Chidambaram SB
    PLoS One, 2019;14(9):e0220995.
    PMID: 31487305 DOI: 10.1371/journal.pone.0220995
    Parkinson's disease (PD) is an irreversible and incurable multigenic neurodegenerative disorder. It involves progressive loss of mid brain dopaminergic neurons in the substantia nigra pars compacta (SN). We compared brain gene expression profiles with those from the peripheral blood cells of a separate sample of PD patients to identify disease-associated genes. Here, we demonstrate the use of gene expression profiling of brain and blood for detecting valid targets and identifying early PD biomarkers. Implementing this systematic approach, we discovered putative PD risk genes in brain, delineated biological processes and molecular functions that may be particularly disrupted in PD and also identified several putative PD biomarkers in blood. 20 of the differentially expressed genes in SN were also found to be differentially expressed in the blood. Further application of this methodology to other brain regions and neurological disorders should facilitate the discovery of highly reliable and reproducible candidate risk genes and biomarkers for PD. The identification of valid peripheral biomarkers for PD may ultimately facilitate early identification, intervention, and prevention efforts as well.
    Matched MeSH terms: Brain/drug effects; Brain/metabolism; Brain/physiopathology
  7. Mumtaz W, Xia L, Mohd Yasin MA, Azhar Ali SS, Malik AS
    PLoS One, 2017;12(2):e0171409.
    PMID: 28152063 DOI: 10.1371/journal.pone.0171409
    Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant's treatment outcome may help during antidepressant's selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant's treatment outcome for the MDD patients.
    Matched MeSH terms: Brain/physiopathology
  8. Shadli RM, Pieter MS, Yaacob MJ, Rashid FA
    Brain Inj, 2011;25(6):596-603.
    PMID: 21534737 DOI: 10.3109/02699052.2011.572947
    The influence of apolipoprotein (APOE) on neuropsychological outcome was investigated in 19 patients (25.79 ± 7.22 years) with mild-to-moderate traumatic brain injury and 14 matched healthy control subjects (27.43 ± 6.65 years).
    Matched MeSH terms: Brain Injuries/genetics*; Brain Injuries/epidemiology; Brain Injuries/physiopathology
  9. Zak J, Vives V, Szumska D, Vernet A, Schneider JE, Miller P, et al.
    Cell Death Differ, 2016 Dec;23(12):1973-1984.
    PMID: 27447114 DOI: 10.1038/cdd.2016.76
    Chromosomal abnormalities are implicated in a substantial number of human developmental syndromes, but for many such disorders little is known about the causative genes. The recently described 1q41q42 microdeletion syndrome is characterized by characteristic dysmorphic features, intellectual disability and brain morphological abnormalities, but the precise genetic basis for these abnormalities remains unknown. Here, our detailed analysis of the genetic abnormalities of 1q41q42 microdeletion cases identified TP53BP2, which encodes apoptosis-stimulating protein of p53 2 (ASPP2), as a candidate gene for brain abnormalities. Consistent with this, Trp53bp2-deficient mice show dilation of lateral ventricles resembling the phenotype of 1q41q42 microdeletion patients. Trp53bp2 deficiency causes 100% neonatal lethality in the C57BL/6 background associated with a high incidence of neural tube defects and a range of developmental abnormalities such as congenital heart defects, coloboma, microphthalmia, urogenital and craniofacial abnormalities. Interestingly, abnormalities show a high degree of overlap with 1q41q42 microdeletion-associated abnormalities. These findings identify TP53BP2 as a strong candidate causative gene for central nervous system (CNS) defects in 1q41q42 microdeletion syndrome, and open new avenues for investigation of the mechanisms underlying CNS abnormalities.
    Matched MeSH terms: Brain/abnormalities; Brain/pathology
  10. Mohd Said MR, Abdul Rani R, Raja Ali RA, Ngiu CS
    Med J Malaysia, 2017 02;72(1):77-79.
    PMID: 28255151 MyJurnal
    Percutaneous Endoscopic Gastrostomy (PEG) tubes were often offered to patients requiring long term enteral feeding. Even though the procedure is relatively safe, it is associated with various complications such as peritonitis or even death.1 We presented a case of a 54-year-old gentleman with underlying ischemic stroke and pus discharges from a recently inserted PEG tube. Computed Topography (CT) scan confirmed abdominal wall necrotising fasciitis complicated with hyperosmolar hyperglycaemia state (HHS) and later succumbed after 48 hours of admission. Our case illustrated the rare complication related to the insertion of PEG tube; abdominal wall necrotising fasciitis that was associated with mortality.
    Matched MeSH terms: Brain Ischemia
  11. Jalaei B, Zakaria MN, Sidek D
    Iran J Otorhinolaryngol, 2017 Jan;29(90):53-57.
    PMID: 28229064
    INTRODUCTION: Noonan syndrome (NS) is a heterogeneous genetic disease that affects many parts of the body. It was named after Dr. Jacqueline Anne Noonan, a paediatric cardiologist.

    CASE REPORT: We report audiological tests and auditory brainstem response (ABR) findings in a 5-year old Malay boy with NS. Despite showing the marked signs of NS, the child could only produce a few meaningful words. Audiological tests found him to have bilateral mild conductive hearing loss at low frequencies. In ABR testing, despite having good waveform morphology, the results were atypical. Absolute latency of wave V was normal but interpeak latencies of wave's I-V, I-II, II-III were prolonged. Interestingly, interpeak latency of waves III-V was abnormally shorter.

    CONCLUSION: Abnormal ABR results are possibly due to abnormal anatomical condition of brainstem and might contribute to speech delay.

    Matched MeSH terms: Brain Stem; Evoked Potentials, Auditory, Brain Stem
  12. Lai CD, Marret MJ, Jayanath S, Azanan MS
    Child Abuse Negl, 2023 Nov;145:106434.
    PMID: 37657172 DOI: 10.1016/j.chiabu.2023.106434
    BACKGROUND: Abusive head trauma (AHT) is a major cause of traumatic brain injury in infancy. This exploratory study compared standardized developmental assessment versus functional outcome assessment between 18 months and 5 years of age following AHT in infancy.

    METHODS: Observational cross-sectional study after surviving AHT in infancy. Seventeen children between 18 months and 5 years of age underwent clinical examination, developmental assessment using the Schedule of Growing Skills II (SGS II) and functional assessment using the Glasgow Outcome Scale-Extended Pediatric Revision (GOS-E Peds). Additional clinical information was extracted from medical records.

    RESULTS: Age at assessment ranged from 19 to 53 months (median 26 months). Most (n = 14) were delayed in at least 1 domain, even without neurological or visual impairment or visible cortical injury on neuroimaging, including 8 children with favourable GOS-E Peds scores. The most affected domain was hearing and language. Delay in the manipulative domain (n = 6) was associated with visual and/or neurological impairment and greater severity of delay across multiple domains. Eleven (64.7 %) had GOS-E Peds scores indicating good recovery, with positive correlation between GOS-Peds scores and number of domains delayed (r = 0.805, p 

    Matched MeSH terms: Brain Injuries, Traumatic*
  13. Mohammad Hanafiah, Mohd Farhan Hamdan, Azura Mohamed Mukhari Shahizon, Wong, Sau Wei, Yoganathan Kanaheswari
    Neurology Asia, 2018;23(2):179-184.
    MyJurnal
    Granulomatous amoebic encephalitis caused by Acanthamoeba is a rare entity mainly affecting
    immunocompromised patients. We reported a case of Acanthamoeba encephalitis of a 1-year-old
    immunocompetent child and described the CT and MRI findings of the brain, while reviewing the
    relevant literatures. The imaging findings of Acanthamoeba meningoencepalitis in immunocompetent
    patients are non-specific and pose a diagnostic challenge.
    Matched MeSH terms: Brain
  14. Radzak S, Khair Z, Ahmad F, Idris Z, Yusoff A
    Turk Neurosurg, 2021;31(1):99-106.
    PMID: 33491172 DOI: 10.5137/1019-5149.JTN.27893-20.4
    AIM: To determine the mitochondrial microsatellite instability (mtMSI) status in a series of Malaysian patients with brain tumors. Furthermore, we analyzed whether the mtMSI status is associated with the clinicopathological features of the patients.

    MATERIAL AND METHODS: Forty fresh frozen tumor tissues along with blood samples of brain tumor patients were analyzed for mtMSI by PCR amplification of genomic DNAs, and the amplicons were directly sequenced in both directions using Sanger sequencing.

    RESULTS: Microsatellite analysis revealed that 20% (8 out of 40) of the tumors were mtMSI positive with a total of 8 mtMSI changes. All mtMSI markers were detected in D310 and D16184 of the D-loop region. Additionally, no significant association was observed between mtMSI status and clinicopathological features.

    CONCLUSION: The variations, specifically the mtMSI, suggest that the mitochondrial DNA (mtDNA) can be targeted for genomic alteration in brain tumors. Therefore, the specific role of mtDNA alteration in brain tumor development and prognosis requires further investigation.

    Matched MeSH terms: Brain Neoplasms/diagnosis; Brain Neoplasms/genetics*; Brain Neoplasms/epidemiology*
  15. Nilashi M, Ibrahim O, Ahani A
    Sci Rep, 2016 Sep 30;6:34181.
    PMID: 27686748 DOI: 10.1038/srep34181
    Parkinson's disease (PD) is a member of a larger group of neuromotor diseases marked by the progressive death of dopamineproducing cells in the brain. Providing computational tools for Parkinson disease using a set of data that contains medical information is very desirable for alleviating the symptoms that can help the amount of people who want to discover the risk of disease at an early stage. This paper proposes a new hybrid intelligent system for the prediction of PD progression using noise removal, clustering and prediction methods. Principal Component Analysis (PCA) and Expectation Maximization (EM) are respectively employed to address the multi-collinearity problems in the experimental datasets and clustering the data. We then apply Adaptive Neuro-Fuzzy Inference System (ANFIS) and Support Vector Regression (SVR) for prediction of PD progression. Experimental results on public Parkinson's datasets show that the proposed method remarkably improves the accuracy of prediction of PD progression. The hybrid intelligent system can assist medical practitioners in the healthcare practice for early detection of Parkinson disease.
    Matched MeSH terms: Brain
  16. Perumal R, Bhattathiry EP
    Med J Malaya, 1970 Mar;24(3):208-11.
    PMID: 4246803
    Matched MeSH terms: Brain/metabolism
  17. Li Y, Tian Q, Li Z, Dang M, Lin Y, Hou X
    Drug Dev Res, 2019 09;80(6):837-845.
    PMID: 31301179 DOI: 10.1002/ddr.21567
    The objective of this study was to evaluate the neuroprotective effect of sitagliptin (Sita), quercetin (QCR) and its combination in β-amyloid (Aβ) induced Alzheimer's disease (AD). Male Sprague-Dawley rats, weighing between 220 and 280 g were used for experiment. Rats were divided into 5 groups (n = 10) and the groups were as follows: (a) Sham control; (b) Aβ injected; (c) Aβ injected + Sita 100; (d) Aβ injected + QCR 100; and (e) Aβ injected + Sita 100 + QCR 100. Cognitive performance was observed by the Morris water maze (MWM), biochemical markers, for example, MDA, SOD, CAT, GSH, Aβ1-42 level, Nrf2/HO-1 expression and histopathological study of rat brain were estimated. Pretreatment with Sita, QCR and their combination showed a significant increase in escape latency in particular MWM cognitive model. Further co-administration of sita and QCR significantly reduced Aβ1-42 level when compared with individual treatment. Biochemical markers, for example, increased SOD, CAT and GSH, decreased MDA were seen, and histopathological studies revealed the reversal of neuronal damage in the treatment group. Additionally, Nrf2/HO-1 pathway in rat's brain was significantly increased by Sita, QCR and their combination. Pretreatment with QCR potentiates the action of Sita in Aβ induced AD in rats. The improved cognitive memory could be because of the synergistic effect of the drugs by decreasing Aβ1-42 level, antioxidant activity and increased expression of Nrf2/HO-1 in rat brain.
    Matched MeSH terms: Brain/drug effects; Brain/metabolism; Brain/pathology
  18. Yan EB, Frugier T, Lim CK, Heng B, Sundaram G, Tan M, et al.
    J Neuroinflammation, 2015 May 30;12:110.
    PMID: 26025142 DOI: 10.1186/s12974-015-0328-2
    During inflammation, the kynurenine pathway (KP) metabolises the essential amino acid tryptophan (TRP) potentially contributing to excitotoxicity via the release of quinolinic acid (QUIN) and 3-hydroxykynurenine (3HK). Despite the importance of excitotoxicity in the development of secondary brain damage, investigations on the KP in TBI are scarce. In this study, we comprehensively characterised changes in KP activation by measuring numerous metabolites in cerebrospinal fluid (CSF) from TBI patients and assessing the expression of key KP enzymes in brain tissue from TBI victims. Acute QUIN levels were further correlated with outcome scores to explore its prognostic value in TBI recovery.

    METHODS: Twenty-eight patients with severe TBI (GCS ≤ 8, three patients had initial GCS = 9-10, but rapidly deteriorated to ≤8) were recruited. CSF was collected from admission to day 5 post-injury. TRP, kynurenine (KYN), kynurenic acid (KYNA), QUIN, anthranilic acid (AA) and 3-hydroxyanthranilic acid (3HAA) were measured in CSF. The Glasgow Outcome Scale Extended (GOSE) score was assessed at 6 months post-TBI. Post-mortem brains were obtained from the Australian Neurotrauma Tissue and Fluid Bank and used in qPCR for quantitating expression of KP enzymes (indoleamine 2,3-dioxygenase-1 (IDO1), kynurenase (KYNase), kynurenine amino transferase-II (KAT-II), kynurenine 3-monooxygenase (KMO), 3-hydroxyanthranilic acid oxygenase (3HAO) and quinolinic acid phosphoribosyl transferase (QPRTase) and IDO1 immunohistochemistry.

    RESULTS: In CSF, KYN, KYNA and QUIN were elevated whereas TRP, AA and 3HAA remained unchanged. The ratios of QUIN:KYN, QUIN:KYNA, KYNA:KYN and 3HAA:AA revealed that QUIN levels were significantly higher than KYN and KYNA, supporting increased neurotoxicity. Amplified IDO1 and KYNase mRNA expression was demonstrated on post-mortem brains, and enhanced IDO1 protein coincided with overt tissue damage. QUIN levels in CSF were significantly higher in patients with unfavourable outcome and inversely correlated with GOSE scores.

    CONCLUSION: TBI induced a striking activation of the KP pathway with sustained increase of QUIN. The exceeding production of QUIN together with increased IDO1 activation and mRNA expression in brain-injured areas suggests that TBI selectively induces a robust stimulation of the neurotoxic branch of the KP pathway. QUIN's detrimental roles are supported by its association to adverse outcome potentially becoming an early prognostic factor post-TBI.

    Matched MeSH terms: Brain/metabolism; Brain Injuries/diagnosis*; Brain Injuries/metabolism*; Brain Injuries/physiopathology
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