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The underlying mechanisms of secondary neuronal damage following intracerebellar hemorrhage (ICbH) have not yet been clearly understood. Our previous study reported apoptotic neuronal damage in the perihematomal region (PH) in mice. However, the possible key factors causing secondary neuronal damage in ICbH are not yet known. Therefore, we aimed to study the vital factors in the mediation of secondary neuronal damage following ICbH induced by collagenase type VII (0.4 U/μL of saline) into the cerebellum of mice. The mice were grouped into four groups: (1) control group (n = 12), (2) day-1 group (n = 12), (3) day-3 group (n = 12), and (4) day-7 group (n = 12). All mice underwent behavior assessment following induction of ICbH and were subsequently sacrificed on days 1, 3, and 7. Perihaematoma samples were collected to study morphological changes, immunohistochemistry, nitric oxide (NO) estimation, and oxidative stress markers, respectively. Mouse behavior was disturbed following ICbH on days 3 and 7 compared to the control. In addition, neuronal damage was found in the PH region. Glial fibrillary acidic protein (GFAP) and excitatory amino acid transporter 1 (EAAT1) were highly expressed on day 7, while gamma-aminobutyric acid receptor subunit alpha-1 (GABAAα1)-containing receptor subunit was detected on days 1 and 3. NO increased on day 1 post-induction and decreased on days 3 and 7. The expressions of superoxide dismutase (SOD), catalase (CAT), neuronal nitric oxide synthases (nNOSs), glutathione peroxidase 1, and cyclooxygenase-2 (COX-2) were significantly increased on day 3. Morphological studies of the PH and tissue showed that neuronal damage occurred from day 1 onward and peaked on day 3, associated with alterations in NO, reactive astrocytes (GFAP), glutamate transport regulation (EAAT1), and GABA receptor. Briefly, significant changes in the key markers in the PH regions at different time points are possibly crucial factors facilitating secondary neuronal damage in the PH region. Identifying the time window of these vital changes could help prevent secondary damage and optimize the treatment to occur at proper time points.

Abstract Background Post-stroke complications affect the informal caregivers equally as the stroke survivors, especially those who have a moderate to worst prognosis in functional capacity recovery. Caregiver Assessment of Function and Upset (CAFU) is one of the common tools used in both research and clinical practice to measure the patient’s dependency level and the stroke caregivers' upset level. Objective This study aimed to translate and validate the CAFU instrument into the Malay language and test the validity and reliability of the CAFU among informal stroke caregivers in Malaysia. Methods A standard forward-backward translation method was employed to translate CAFU. Subsequently, 10 expert panels were included in the validation process, and thereafter reliability testing was conducted among 51 stroke caregivers. The validation of the instrument was determined by computing the content validity indices (CVIs), and we used the Cronbach’s alpha method to explore the internal consistency of the overall score and subscales scores of the Malay-CAFU. Finally, the explanatory factor analysis used principal component extraction and a varimax rotation to examine construct validity. Results All items of the Malay-CAFU had satisfactory item-level CVI (I-CVI), with values greater than 0.80, and the scale-level CVI (S-CVI) was 0.95. These results indicate that the Malay-CAFU had good relevancy. The internal consistency for the reliability test showed a Cronbach’s alpha value of 0.95 for the overall score. The eigenvalues and scree plot supported a two-factor structural model of the instrument. From the explanatory factor analysis, the factor loadings ranged from 0.82 to 0.90 and 0.56 to 0.83, respectively. Conclusion The Malay-CAFU questionnaire is a valid and reliable instrument to assess the dependence level of stroke survivors and the upset level of informal stroke caregivers in Malaysia.

Light is an electromagnetic radiation that has visible and invisible wavelength spectrums. Visible light can only be detected by the eyes through the optic pathways. With the presence of the scalp, cranium, and meninges, the brain is seen as being protected from direct exposure to light. For that reason, the brain can be viewed as a black body lying inside a black box. In physics, a black body tends to be in thermal equilibrium with its environment and can tightly regulate its temperature via thermodynamic principles. Therefore, a healthy brain inside a black box should not be exposed to light. On the contrary, photobiomodulation, a form of light therapy for the brain, has been shown to have beneficial effects on some neurological conditions. The proposed underlying mechanisms are multiple. Herein, we present our intraoperative findings of rapid electrocorticographic brainwave changes when the brain was shone directly with different wavelengths of light during awake brain surgery. Our findings provide literature evidence for light’s ability to influence human brain energy and function. Our proposed mechanism for these rapid changes is the presence of plasma-like energy inside the brain, which causes fast brain activities that are akin to lightning strikes.

As neurotechnologies have gotten better, a lot of neuroscientific research has been done using these new technologies. Even though labs all over the world produce a lot of neuro-data, most of this data has not been shared to help people from different fields understand neuroscience. The neuro-data sharing is essential because it accelerates the pace of discovery in neuroscience. Effective data sharing will depend on the standardized use of file or data formats, highly reusable data analytics tools, and data storage formats. In this review paper, we review the four domains (data format, data model, data repository, and data analytics) that are currently in use in the neuroscience community. In the end, we are discussing several challenges associated with data sharing.

BackgroundImpairment in cognitive function is a recognized outcome of traumatic brain injury (TBI). However, the degree of impairment has variable relationship with TBI severity and time post injury. The underlying pathology is often due to diffuse axonal injury that has been found even in mild TBI. In this study, we examine the state of white matter putative connectivity in patients with non-severe TBI in the subacute phase, i.e., within 10 weeks of injury and determine its relationship with neuropsychological scores.MethodsWe conducted a case-control prospective study involving 11 male adult patients with non-severe TBI and an age-matched control group of 11 adult male volunteers. Diffusion MRI scanning and neuropsychological tests were administered within 10 weeks post injury. The difference in fractional anisotropy (FA) values between the patient and control groups was examined using tract-based spatial statistics. The FA values that were significantly different between patients and controls were then correlated with neuropsychological tests in the patient group.ResultsSeveral clusters with peak voxels of significant FA reductions (p < 0.05) in the white matter skeleton were seen in patients compared to the control group. These clusters were located in the superior fronto-occipital fasciculus, superior longitudinal fasciculus, uncinate fasciculus, and cingulum, as well as white matter fibers in the area of genu of corpus callosum, anterior corona radiata, superior corona radiata, anterior thalamic radiation and part of inferior frontal gyrus. Mean global FA magnitude correlated significantly with MAVLT immediate recall scores while matrix reasoning scores correlated positively with FA values in the area of right superior fronto-occipital fasciculus and left anterior corona radiata.ConclusionThe non-severe TBI patients had abnormally reduced FA values in multiple regions compared to controls that correlated with several measures of executive function during the sub-acute phase of TBI.

This paper extends frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack of geographical diversity precluded accounting for site-specific variance, increasing qEEG nuisance variance. We ameliorate these weaknesses. (i) Create lifespan Riemannian multinational qEEG norms for cross-spectral tensors. These norms result from the HarMNqEEG project fostered by the Global Brain Consortium. We calculate the norms with data from 9 countries, 12 devices, and 14 studies, including 1564 subjects. Instead of raw data, only anonymized metadata and EEG cross-spectral tensors were shared. After visual and automatic quality control, developmental equations for the mean and standard deviation of qEEG traditional and Riemannian DPs were calculated using additive mixed-effects models. We demonstrate qEEG “batch effects” and provide methods to calculate harmonized z-scores. (ii) We also show that harmonized Riemannian norms produce z-scores with increased diagnostic accuracy predicting brain dysfunction produced by malnutrition in the first year of life and detecting COVID induced brain dysfunction. (iii) We offer open code and data to calculate different individual z-scores from the HarMNqEEG dataset. These results contribute to developing bias-free, low-cost neuroimaging technologies applicable in various health settings.

Bone marrow-derived mesenchymal stem cells (BMSCs) have therapeutic potential for spinal cord injury (SCI). We have shown that insulin-like growth factor 1 (IGF-1) enhances the cellular proliferation and survivability of BMSCs-derived neural progenitor cells (NPCs) by downregulating miR-22-3p. However, the functional application of BMSCs-derived NPCs has not been investigated fully. In this study, we demonstrate that knockdown of endogenous miR-22-3p in BMSCs-derived NPCs upregulates Akt1 expression, leading to enhanced cellular proliferation. RNASeq analysis reveals 3,513 differentially expressed genes in NPCs. The upregulated genes in NPCs enrich the gene ontology term associated with nervous system development. Terminally differentiated NPCs generate cells with neuronal-like morphology and phenotypes. Transplantation of NPCs in the SCI rat model results in better recovery in locomotor and sensory functions 4 weeks after transplantation. Altogether, the result of this study demonstrate that NPCs derived with IGF-1 supplementation could be differentiated into functional neural lineage cells and are optimal for stem cell therapy in SCI.

Reliable prediction of traumatic brain injury (TBI) outcomes based on machine learning (ML) that is derived from quantitative electroencephalography (EEG) features has renewed interest in recent years. Nevertheless, the approach has suffered from imbalanced datasets. Hence, to get a reliable predictive model for predicting outcomes, specifically in a high proportion of moderate TBI with good outcomes, could be challenging. This work proposes an improved outcome predictive model that combines the absolute power spectral density (PSD) as input features for training random under-sampling boosting decision trees (RUSBoosted Trees) as a classifier. Resting-state, eyes-closed EEG data were obtained from 27 moderate TBI patients with follow-up visits. Patient outcome at 4–10 weeks to 12-month was dichotomized based on the Glasgow Outcome Scale as poor (GOS score ≤ 4) and good outcomes (GOS score = 5). The predictive values of absolute PSD from five frequency bands: $\delta $ (0.5-4Hz), $\theta $ (4-7Hz), $\alpha $ (7-13Hz), $\beta $ (13-30Hz) and $\gamma $ (30–100Hz) were evaluated to identify the most informative predictors for reliable prediction outcomes. RUSBoosted Trees performed best at discriminating patients into two outcomes categories (G-Mean = 92.95%, TPrate = 100%, TNrate = 86.4%) of absolute PSD in $\delta $ and $\gamma $ bands, which was excellent compared to the other state-of-the-art methods. The highest area under the curve (AUC) of absolute PSD in $\delta $ (AUC $_\delta =0.97$ ) and $\gamma $ (AUC $_\gamma =0.95$ ) revealed their predictive values as robust prognostic markers for prediction outcomes. The RUSBoosted Trees presents a promising result in prognosis prediction of highly imbalanced data, making it an accessible prediction tool for clinical decision-making, unlike the black-box approaches.

A sudden blow or jolt to the human brain called traumatic brain injury (TBI) is one of the most common injuries recorded in the health insurance claim. Generally, computed tomography (CT) or magnetic resonance imaging (MRI) is required to identify the trauma's severity. Unfortunately, CT and MRI equipment are bulky, expensive, and not always available, limiting their use in TBI detection. Therefore, as an alternative, this study presents a novel classification architecture that can classify non-severe TBI patients from healthy subjects by using resting-state electroencephalogram (EEG) as the input. The proposed architecture employs a convolutional neural network (CNN), and error-correcting output codes support vector machine (ECOC-SVM) to perform automated feature extraction and multi-class classification. In this architecture, complex feature selection and extraction steps are avoided. The proposed architecture attained a high-performance classification accuracy of 99.76%, potentially being used as a classification approach to preventing healthcare insurance fraud. The proposed method is compared to existing studies in the literature. The outcome from the comparisons indicates that the proposed method has outperformed the benchmarked methods by presenting the highest classification accuracy and precision.

Abstract Introduction Mesenchymal stem cells (MSCs) isolated from bone marrow have different developmental origins, including neural crest. MSCs can differentiate into neural progenitor-like cells (NPCs) under the influence of bFGF and EGF. NPCs can terminally differentiate into neurons that express beta-III-tubulin and elicit action potential. The main aim of the study was to identify key genetic markers involved in differentiation of MSCs into NPCs through transcriptomic analysis. Method Total RNA was isolated from MSCs and MSCs-derived NPCs followed by cDNA library construction for transcriptomic analysis. Sample libraries that passed the quality and quantity assessments were subjected to high throughput mRNA sequencing using NextSeq®500. Differential gene expression analysis was performed using the DESeq2 R package with MSC samples being a reference group. The expression of eight differentially regulated genes was counter validated using real-time PCR. Results In total, of the 3,252 differentially regulated genes between MSCs and NPCs with two or more folds, 1,771 were upregulated genes, whereas 1,481 were downregulated in NPCs. Amongst these differential genes, 104 transcription factors were upregulated, and 45 were downregulated in NPCs. Neurogenesis related genes were upregulated in NPCs and the main non-redundant gene ontology (GO) terms enriched in NPCs were the autonomic nervous system, cell surface receptor signalling pathways), extracellular structure organisation, and programmed cell death. The main non-redundant GO terms enriched in MSCs included cytoskeleton organisation cytoskeleton structural constituent, mitotic cell cycle), and the mitotic cell cycle process Gene set enrichment analysis also confirmed cell cycle regulated pathways as well as Biocarta integrin pathway were upregulated in MSCs. Transcription factors enrichment analysis by ChEA3 revealed Foxs1 and HEYL, amongst the top five transcription factors, inhibits and enhances, respectively, the NPCs differentiation of MSCs. Conclusions The vast differences in the transcriptomic profiles between NPCs and MSCs revealed a set of markers that can identify the differentiation stage of NPCs as well as provide new targets to enhance MSCs differentiation into NPCs.

Purpose – Advanced medical technology has reduced the mortality rate among traumatic brain injury (TBI) patients. This, however, has led to an increasing number of surviving patients with a major disability. As a consequence, these patients need attentive care which becomes an important issue for the society, particularly family members. Thus, this paper aims to review some of the salient roles, challenges and needs of the family caregivers in caring or nursing for their family members diagnosed with TBI. Design/methodology/approach – An inclusive search of the literature was undertaken to identify the family roles, challenges and needs in supporting and nursing TBI patients. Findings – Previous studies have shown that the family needs to address two important aspects of taking care of TBI patients, which involve emotional and physical affairs. Hence, it is essential for the family members to have adequate information on healing treatment, nursing and care methods, financial support, support groups, managing self-care and, more importantly, emotional and social support. Originality/value – This paper is not currently under consideration, in press or published elsewhere. In Malaysian culture, nursing disabled patients have always been a family responsibility. The role of nursing the patients has been done domestically and is considered a private affair. In order to execute the role, some put the patient needs as their priority and leave aside their needs and matters.

The debilitating effect of traumatic brain injury (TBI) extends years after the initial injury and hampers the recovery process and quality of life. In this study, we explore the functional reorganization of the default mode network (DMN) of those affected with non-severe TBI. Traumatic brain injury (TBI) is a wide-spectrum disease that has heterogeneous effects on its victims and impacts everyday functioning. The functional disruption of the default mode network (DMN) after TBI has been established, but its link to causal effective connectivity remains to be explored. This study investigated the differences in the DMN between healthy participants and mild and moderate TBI, in terms of functional and effective connectivity using resting-state functional magnetic resonance imaging (fMRI). Nineteen non-severe TBI (mean age 30.84 ± 14.56) and twenty-two healthy (HC; mean age 27.23 ± 6.32) participants were recruited for this study. Resting-state fMRI data were obtained at the subacute phase (mean days 40.63 ± 10.14) and analyzed for functional activation and connectivity, independent component analysis, and effective connectivity within and between the DMN. Neuropsychological tests were also performed to assess the cognitive and memory domains. Compared to the HC, the TBI group exhibited lower activation in the thalamus, as well as significant functional hypoconnectivity between DMN and LN. Within the DMN nodes, decreased activations were detected in the left inferior parietal lobule, precuneus, and right superior frontal gyrus. Altered effective connectivities were also observed in the TBI group and were linked to the diminished activation in the left parietal region and precuneus. With regard to intra-DMN connectivity within the TBI group, positive correlations were found in verbal and visual memory with the language network, while a negative correlation was found in the cognitive domain with the visual network. Our results suggested that aberrant activities and functional connectivities within the DMN and with other RSNs were accompanied by the altered effective connectivities in the TBI group. These alterations were associated with impaired cognitive and memory domains in the TBI group, in particular within the language domain. These findings may provide insight for future TBI observational and interventional research.

Although traumatic brain injury (TBI) is a global public health issue, not all injuries necessitate additional hospitalisation. Thinking, memory, attention, personality, and movement can all be negatively impacted by TBI. However, only a small proportion of nonsevere TBIs necessitate prolonged observation. Clinicians would benefit from an electroencephalography (EEG)-based computational intelligence model for outcome prediction by having access to an evidence-based analysis that would allow them to securely discharge patients who are at minimal risk of TBI-related mortality. Despite the increasing popularity of EEG-based deep learning research to create predictive models with breakthrough performance, particularly in epilepsy prediction, its use in clinical decision making for the diagnosis and prognosis of TBI has not been as widely exploited. Therefore, utilising 60s segments of unprocessed resting-state EEG data as input, we suggest a long short-term memory (LSTM) network that can distinguish between improved and unimproved outcomes in moderate TBI patients. Complex feature extraction and selection are avoided in this architecture. The experimental results show that, with a classification accuracy of 87.50 ± 0.05%, the proposed prognostic model outperforms three related works. The results suggest that the proposed methodology is an efficient and reliable strategy to assist clinicians in creating an automated tool for predicting treatment outcomes from EEG signals.

Natural products remain a crucial source of drug discovery for accessible and affordable solutions for healthy aging. Centella asiatica (L.) Urb. (CA) is an important medicinal plant with a wide range of ethnomedicinal uses. Past in vivo and in vitro studies have shown that the plant extract and its key components, such as asiatic acid, asiaticoside, madecassic acid and madecassoside, exhibit a range of anti-inflammatory, neuroprotective, and cognitive benefits mechanistically linked to mitoprotective and antioxidant properties of the plant. Mitochondrial dysfunction and oxidative stress are key drivers of aging and neurodegenerative disease, including Alzheimer’s disease and Parkinson’s disease. Here we appraise the growing body of evidence that the mitoprotective and antioxidative effects of CA may potentially be harnessed for the treatment of brain aging and neurodegenerative disease.

Approximately one in five children worldwide suffers from childhood malnutrition and its complications, including increased susceptibility to inflammation and infectious diseases. Due to improved early interventions, most of these children now survive early malnutrition, even in low-resource settings (LRS). However, many continue to exhibit neurodevelopmental deficits, including low IQ, poor school performance, and behavioral problems over their lifetimes. Most studies have relied on neuropsychological tests, school performance, and mental health and behavioral measures. Few studies, in contrast, have assessed brain structure and function, and to date, these have mainly relied on low-cost techniques, including electroencephalography (EEG) and evoked potentials (ERP). The use of more advanced methods of neuroimaging, including magnetic resonance imaging (MRI) and functional near-infrared spectroscopy (fNIRS), has been limited by cost factors and lack of availability of these technologies in developing countries, where malnutrition is nearly ubiquitous. This report summarizes the current state of knowledge and evidence gaps regarding childhood malnutrition and the study of its impact on neurodevelopment. It may help to inform the development of new strategies to improve the identification, classification, and treatment of neurodevelopmental disabilities in underserved populations at the highest risk for childhood malnutrition.

Forensic facial approximation was applied to a 5000-year-old female skull from a shell midden in Guar Kepah, Malaysia. The skull was scanned using a computed tomography (CT) scanner in the Radiology Department of the Hospital Universiti Sains Malaysia using a Light Speed Plus scanner with a 1 mm section thickness in spiral mode and a 512 × 512 matrix. The resulting images were stored in Digital Imaging and Communications in Medicine (DICOM) format. A three-dimensional (3D) model of the skull was obtained from the CT scan data using Blender’s 3D modelling and animation software. After the skull was reconstructed, it was placed on the Frankfurt plane, and soft tissue thickness markers were placed based on 34 Malay CT scan data of the nose and lips. The technique based on facial approximation by data extracted from facial measurements of living individuals showed greater anatomical coherence when combined with anatomical deformation. The facial approximation in this study will pave the way towards understanding face prediction based on skull structures, soft tissue prediction rules, and soft tissue thickness descriptors.

Intracerebral haemorrhage (ICH) or haemorrhagic stroke can be managed medically or by surgical evacuation of the hematoma. However, several authors have reported no significant difference when compared between both interventions in haemorrhagic stroke patients. We aimed to assess the use of Transcranial Magnetic Simulation (TMS) as supportive of medical and surgical interventions to assist the rehabilitation process in haemorrhagic stroke patient. A randomized control trial was performed on twenty nine patients and randomized into three groups; (1)Facilitatory, (2)Inhibitory and (3)Sham group. Patient underwent two weeks of TMS Stimulation protocol for total of 10 sessions. The pre and post Motor Evoked Potential (MEP) reading between groups were compared and analyzed. Our result indicated that regardless of patient’s age and ICH clot size, the improvement in MEP score after TMS facilitatory protocol was significantly higher compared to the Sham protocol group (p = 0.02). Such correlation however, was not observed in the inhibitory protocol group (p = 0.175). Collectively, our finding had demonstrates TMS potential as a safe and non-invasive tool for supportive management of ICH stroke as patients and that patient with stable ICH will have better motor function recovery post rTMS facilitatory protocol regardless of their age and clot size. Keywords: Transcranial magnetic stimulation, Motor evoked potential, Intracranial haemorrhage, Stroke rehabilitation, Facilitatory, Inhibitory

Background: Because nearly 23,000 more neurosurgeons are needed globally to address 5 million essential neurosurgical cases that go untreated each year, there is an increasing interest in task-shifting and task-sharing (TS/S), delegating neurosurgical tasks to nonspecialists, particularly in low- and middle-income countries (LMICs). This global survey aimed to provide a cross-sectional understanding of the prevalence and structure of current neurosurgical TS/S practices in LMICs. Methods: The survey was distributed to a convenience sample of individuals providing neurosurgical care in LMICs with a Web-based survey link via electronic mailing lists of continental societies and various neurosurgical groups, conference announcements, e-mailing lists, and social media platforms. Country-level data were analyzed by descriptive statistics. Results: The survey yielded 127 responses from 47 LMICs; 20 countries (42.6%) reported ongoing TS/S. Most TS/S procedures involved emergency interventions, the top 3 being burr holes, craniotomy for hematoma evacuation, and external ventricular drain. Most (65.0%) believed that their Ministry of Health does not endorse TS/S (24.0% unsure), and only 11% believed that TS/S training was structured. There were few opportunities for TS/S providers to continue medical education (11.6%) or maintenance of certification (9.4%, or receive remuneration (4.2%). Conclusions: TS/S is ongoing in many LMICs without substantial structure or oversight, which is concerning for patient safety. These data invite future clinical outcomes studies to assess effectiveness and discussions on policy recommendations such as standardized curricula, certification protocols, specialist oversight, and referral networks to increase the level of TS/S care and to continue to increase the specialist workforce. Key words: Capacity, Global health, Global neurosurgery, LMIC, Task-sharing, Task-shifting, Workforce

Background: Neurosurgical task shifting and task sharing (TS/S), delegating clinical care to non-neurosurgeons, is ongoing in many hospital systems in which neurosurgeons are scarce. Although TS/S can increase access to treatment, it remains highly controversial. This survey investigated perceptions of neurosurgical TS/S to elucidate whether it is a permissible temporary solution to the global workforce deficit. Methods: The survey was distributed to a convenience sample of individuals providing neurosurgical care. A digital survey link was distributed through electronic mailing lists of continental neurosurgical societies and various collectives, conference announcements, and social media platforms (July 2018–January 2019). Data were analyzed by descriptive statistics and univariate regression of Likert Scale scores. Results: Survey respondents represented 105 of 194 World Health Organization member countries (54.1%; 391 respondents, 162 from high-income countries and 229 from low- and middle-income countries [LMICs]). The most agreed on statement was that task sharing is preferred to task shifting. There was broad consensus that both task shifting and task sharing should require competency-based evaluation, standardized training endorsed by governing organizations, and maintenance of certification. When perspectives were stratified by income class, LMICs were significantly more likely to agree that task shifting is professionally disruptive to traditional training, task sharing should be a priority where human resources are scarce, and to call for additional TS/S regulation, such as certification and formal consultation with a neurosurgeon (in person or electronic/telemedicine). Conclusions: Both LMIC and high-income countries agreed that task sharing should be prioritized over task shifting and that additional recommendations and regulations could enhance care. These data invite future discussions on policy and training programs. Key words: Global health, Global neurosurgery, LMIC, Neurotrauma, Task sharing, Task shifting, Workforce

The concept of wholeness or oneness refers to not only humans, but also all of creation. Similarly, consciousness may not wholly exist inside the human brain. One consciousness could permeate the whole universe as limitless energy; thus, human consciousness can be regarded as limited or partial in character. According to the limited consciousness concept, humans perceive projected waves or wave-vortices as a waveless item. Therefore, human limited consciousness collapses the wave function or energy of particles; accordingly, we are only able to perceive them as particles. With this “limited concept”, the wave-vortex or wave movement comes into review, which also seems to have a limited concept, i.e., the limited projected wave concept. Notably, this wave-vortex seems to embrace photonic light, as well as electricity and anything in between them, which gives a sense of dimension to our brain. These elements of limited projected wave-vortex and limitless energy (consciousness) may coexist inside our brain as electric (directional pilot wave) and quantum (diffused oneness of waves) brainwaves, respectively, with both of them giving rise to one brain field. Abnormality in either the electrical or the quantum field or their fusion may lead to abnormal brain function.

Human brain has a complex structure with the billions of neurons, so it is a difficult and challenging task to predict the behavior of human brain. Different methods and classifiers are used to measure and classify the brain activities with higher accuracy and reliability. In this paper, instead of using mostly used classifier (support vector machine), prediction of the brain activity is done by estimating the match score densities. This method is based on likelihood ratio test which helps in finding the optimal combination of match scores. The distributions of match scores are modeled for different classes based on density score fusion in which the densities of different classes are estimated from the training data set and match scores are found by fusing the estimated densities with the testing data. The fusion is done with the data extracted from distributed activation patterns using multivariate pattern analysis (MVPA) against a visual task. MVPA is an intense strategy which helps in better understanding of the human brain. The match score-based technique is used in different biometric systems but never been used for the prediction of brain activity. In order to test the performance of proposed method, prediction accuracy is compared with the support vector machine using two data sets of different modalities, one is electroencephalography (EEG) and the other is functional magnetic resonance imaging (fMRI). The results show that the proposed method predicts the novel data with improved accuracy of 66.1% and 69.3% compared with support vector machine which have 64.15% and 65.7% for fMRI and EEG data sets, respectively.

Traumatic brain injury (TBI) is one of the common injuries when the human head receives an impact due to an accident or fall and is one of the most frequently submitted insurance claims. However, it is often always misused when individuals attempt an insurance fraud claim by providing false medical conditions. Therefore, there is a need for an instant brain condition classification system. This study presents a novel classification architecture that can classify non-severe TBI patients and healthy subjects employing resting-state electroencephalogram (EEG) as the input, solving the immobility issue of the computed tomography (CT) scan and magnetic resonance imaging (MRI). The proposed architecture makes use of long short term memory (LSTM) and error-correcting output coding support vector machine (ECOC-SVM) to perform multiclass classification. The pre-processed EEG time series are supplied to the network by each time step, where important information from the previous time step will be remembered by the LSTM cell. Activations from the LSTM cell is used to train an ECOC-SVM. The temporal advantages of the EEG were amplified and able to achieve a classification accuracy of 100%. The proposed method was compared to existing works in the literature, and it is shown that the proposed method is superior in terms of classification accuracy, sensitivity, specificity, and precision.

Since the concept of working memory was introduced over 50 years ago, different schools of thought have offered different definitions for working memory based on the various cognitive domains that it encompasses. The general consensus regarding working memory supports the idea that working memory is extensively involved in goal-directed behaviors in which information must be retained and manipulated to ensure successful task execution. Before the emergence of other competing models, the concept of working memory was described by the multicomponent working memory model proposed by Baddeley and Hitch. In the present article, the authors provide an overview of several working memory-relevant studies in order to harmonize the findings of working memory from the neurosciences and psychological standpoints, especially after citing evidence from past studies of healthy, aging, diseased, and/or lesioned brains. In particular, the theoretical framework behind working memory, in which the related domains that are considered to play a part in different frameworks (such as memory’s capacity limit and temporary storage) are presented and discussed. From the neuroscience perspective, it has been established that working memory activates the fronto-parietal brain regions, including the prefrontal, cingulate, and parietal cortices. Recent studies have subsequently implicated the roles of subcortical regions (such as the midbrain and cerebellum) in working memory. Aging also appears to have modulatory effects on working memory; age interactions with emotion, caffeine and hormones appear to affect working memory performances at the neurobiological level. Moreover, working memory deficits are apparent in older individuals, who are susceptible to cognitive deterioration. Another younger population with working memory impairment consists of those with mental, developmental, and/or neurological disorders such as major depressive disorder and others. A less coherent and organized neural pattern has been consistently reported in these disadvantaged groups. Working memory of patients with traumatic brain injury was similarly affected and shown to have unusual neural activity (hyper- or hypoactivation) as a general observation. Decoding the underlying neural mechanisms of working memory helps support the current theoretical understandings concerning working memory, and at the same time provides insights into rehabilitation programs that target working memory impairments from neurophysiological or psychological aspects.

Recently there has been growing interest in the differentiation of mesenchymal stem cells (MSCs) into neural lineages. Research suggests that MSCs can be differentiated into neural progenitor-like cells (NPCs) under the specific influence of paracrine factors particularly epidermal growth factor (EGF) and basic fibroblast growth factor (bFGF). Our recent research has found that the addition of insulin-like growth factor 1 (IGF-1) with the combination of the EGF and bFGF could significantly improve the growth and survivability of MSC-derived NPCs. To unravel the molecular mechanism of the improved differentiation we compared the microRNA expression profiles of the differentiation under various combinations of growth factors. MSCs were differentiated into neural lineage in 3 groups; Group A (EGF + bFGF), Group B (EGF + bFGF + IGF-1), and Group C (without growth factor). Regulated microRNAs during the early differentiation were identified by detailed microRNA profiling using Affymetrix GeneChip version 2.0 at three time intervals (day 1, day 3 and day 5). The data were deposited in the Gene Expression Omnibus, series GSE60060.

Intracerebral haemorrhage (ICH) is the most disabling and least treatable form of stroke. Its risk factors include old age, hypertension, diabetes mellitus, hypercholesterolaemia, smoking and high alcohol intake, which are also associated with arterial stiffness. The aim of the present study was to determine the prognostic value of high augmentation index (AI), which is a surrogate marker of arterial stiffness, in patients with spontaneous ICH. Methods: A prospective study of 60 patients with spontaneous supratentorial ICH was conducted. Outcome was assessed using the Modified Rankin Scale at 3 months follow-up. Data were collected on age and sex, risk factors for ICH, clinical parameters, laboratory parameters, radiological findings and hospital management. Logistic regression analysis was carried out to identify independent predictors of 3-month outcome and mortality. Results: Admission Glasgow Coma Scale score (OR, 0.7; 95% CI, 0.450–0.971; p = 0.035), total leukocyte count (OR,1.2; 95% CI, 1.028–1.453; p = 0.023) and haematoma volume (OR, 1.1; 95% CI, 1.024–1.204; p = 0.011) were found to be statistically significant in multivariate analysis of 3-month poor outcome. Factors independently associated with mortality were high AI (OR, 8.6; 95%CI, 1.748–40.940; p = 0.007) and midline shift (OR, 7.5; 95%CI, 1.809–31.004; p = 0.005). Conclusion: Admission Glasgow Coma Scale score, total leukocyte count and haematoma volume were significant predictors for 3-month poor outcome; high AI and midline shift were significant predictors for 3-month mortality.

The aim of this study was to determine the cost-effectiveness of using baseline neuromonitoring (BNM) compared with multimodality monitoring (M3) for severe traumatic brain injury (TBI). METHODS: Sixty-two patients with severe TBI underwent a prospective observational study where they were divided into two groups of patients receiving treatment with M3 (32 patients) and BNM (30 patients). The macro and micro costings were performed on each patient. The Barthel Index score after 1 year was used as an outcome measurement tool for both groups. The cost-effectiveness (CE) ratio was calculated using the Poisson regression model. RESULTS: The costs of equipment and consumables between the groups was statistically significant (p < 0.001) after correcting for age and severity of injury. Other cost categories were not significantly different. The crude CE ratios were 168.66 (95% CI: 168.32, 169.03) and 144.16 (95% CI: 143.87, 144.45) for BNM and M3 respectively. The two crude CE ratios were significantly different (p < 0.001). It was calculated by controlling or adjusting age, gender, Glasgow Coma Score, Marshall's classification at admission and type of injury. The adjusted CE ratios were 171.32 (95% CI: 170.97, 171.68) and 141.50 (95% CI: 141.26, 141.79) for BNM and M3, respectively. The two adjusted CE ratios were significantly different (p < 0.001). CONCLUSION: The application of M3 for severe TBI was more cost-effective than BNM. All calculations were made at 3.8 Malaysian Ringgit (MYR) to the United States dollar (USD).

To determine whether or not multimodality monitoring technique would result in a better outcome score than single modality monitoring in severely head injured patients. Methods: This was a prospective randomized study that included all adults with traumatic severe head injury who had a Glasgow Coma Score < 9 and computed tomography scan features that did not reveal significant infratentorial pathology. Subjects were randomized into a multimodality group where they received multiple cerebral monitoring or into a standard single modality group where they received only intracranial pressure monitoring. The outcome was analysed 6 months post treatment using the Barthel Index. Results: The outcome at 6 months post treatment between the two groups was not statistically significant (p < 0.48). However, the percentage of subjects who were independent at 6 months was higher in the multimodality group (21.2%) compared with the single modality group (17.3%). Conclusion: Multimodality monitoring for severely head-injured patients has no effect on outcome. However, study with a larger sample size and improvement in groups comparison are required to ascertain the above findings.

Mitragyna speciosa Korth, or better known as ketum, has long been used by traditional folk around Southeast Asia to prevent fatigue from working under hot tropical weather and as a replacement of opium, which can then cause addiction. To date, no findings have been reported of the toxic effect of ketum subchronically (28 days). Hence, the aim of this study was to investigate the toxicity of subchronic effect of standardised methanolic extract of ketum (SMEMS) in Sprague-Dawley rats. Rats were orally administered with 100, 200, and 500 mg/kg of SMEMS for 28 days. Body weights were recorded daily. They were terminated at day 28 to obtain data for haematology, biochemistry, and histopathology of the brain, liver, kidney, lung, heart, sciatic nerve, and spinal cord. The SMEMS affected body weight compared to control group. Biochemistry findings showed that liver and kidney were affected with the abnormal values in AST, creatinine, globulin, glucose, total protein, and urea. However, SMEMS produced toxic effect more to liver, kidney, and lung than other organs as observed histopathologically. The results suggested subchronic exposure of ketum is toxic to the physiology of the animals.

The pattern of allelic loss of heterozygosity (LOH) and PTEN mutations appear to be associated with the progression of gliomas leading to a decrement in the survival rate of patients. This present study was carried out to determine the LOH and PTEN mutational status in glioma patients and its association with patients' survival. Methods: Thirty-seven Malaysian glioma patients of the Malay race were subject to PTEN mutational analysis and the presence of LOH using the cold single-strand conformation polymorphism method, and their clinical and paraclinical response were correlated. Results: Among analysed glioma patients, seven (21.6%) cases with PTEN mutations were detected and 12 (32.4%) of 37 patients showed presence of LOH. Univariate analysis showed that tumour grade, vascularization, PTEN mutation, LOH and combination of both PTEN mutation and LOH were significantly associated with glioma patients' survival. Multivariate analysis revealed that no factors contributed to survival time. Conclusion: The results show that PTEN mutation and LOH are quite frequent in Malaysian glioma patients. However, they have no impact on the survival outcome of patients.

To use data from a prospective, longitudinal study to determine whether psychomotor functions improve spontaneously during the first year following paediatric traumatic brain injury without modern rehabilitation facilities in a rural area of Malaysia. Methods: Thirty-six paediatric patients who were referred for neurosurgical management for mild to severe head injuries were studied over a period of 2 years. No patients had orthopaedic or surgical trauma. Assessment of patients occurred at 3, 6 and 12 months, and patients were subjected to the Bender Gestalt Test, Weschler Intelligence Scale for Children-Revised and subtests from the Weschler Preschool and Primary Scale of Intelligence. None of the patients received professional rehabilitation due to a lack of facilities; only traditional treatment was given during this period. Results: There were no significant changes in any of the parameters, except for integration error, after a period of 1 year. Cognitive function improved in 30% of patients after 1 year of follow-up. Despite an increased relationship of the caregiver to the patient in the first year of trauma, there was no general improvement when compared to the Western literature. Conclusion: A lack of modern resources in the community, a low general practitioner to patient ratio, and no inpatient or outpatient rehabilitation services do not lead to spontaneous improvement in the psychomotor condition of our patients despite good interfamily support. These are important findings for the future restructuring of the psychological service in Malaysia.

Background: A new stereotactic frame was created in 2015, based on a linear algorithm. It is called Albert Wong (AW) frame. A simple AW stereo-calculator was also designed based on Excel® (Microscoft Corporation, Redmond, WA) programme for the frame. Objective: The aim of this study is to test the accuracy of the AW frame by a direct head to head comparison with CRW® frame (Integra Life Sciences, Plainsboro, NJ) on a phantom. Methods: This is a prospective pilot cross-sectional phantom study with a total of 42 (21 for AW and 21 for CRW®) laboratory testings performed in 2017 at our institute to compare the accuracies of both frames in a consecutive manner. A phantom (BL phantom) was newly created, where targets can be placed at different heights and positions on a platform attached under the frame for accuracy testing comparing between the AW and CRW1® frames. Results: A comparable accuracy testing results were observed between the AW and CRW1® frames of 0.64 mm versus 1.07 mm respectively. Approval from the local ethics committee for a clinical trial was obtained. We report on three case illustrations who had the AW frame-based biopsies with definitive diagnoses and without any post-biopsy related complication. Conclusion: AW frame successfully demonstrated a good accuracy of 0.64mm in phantom testing using the BL phantom by a linear algorithmic calculation. The clinical trial with three patients demonstrated definitive diagnoses and safety with its use. [ABSTRACT FROM AUTHOR]