A brain tumor is an abnormal mass of tissue found inside the brain that consists of cells that grow and multiply without any control and unchecked by the mechanisms that regulate normal cell growth. It is one of the leading causes of death in many different regions worldwide, affecting various ages, sex, race, or ethnicities. Besides being a life-threatening condition, it can also disrupt normal brain function leading to severe cognitive morbidity. Additionally, the cost associated with active treatment and palliative care of the brain tumor most often proves to be out of reach for many people. Over the past decades, even though we have several published literature showing the epidemiology and characteristics of brain tumors, up-to-date epidemiological data is yet to be published. This review will provide comparable recent statistics regarding the incidence of brain tumors in 3 different regions; - the USA, the UK, and Australia. Also, a focus will be given to brain tumor’s key characteristics, classifications, and treatment protocol.

In this paper, we propose methods for brain tumor detection in MRI images based on ensemble learning. We build upon prior research on ensemble methods by testing the concatenation of pre-trained models: features extracted via transfer learning are merged and segmented by classification algorithms or a stacked ensemble of those algorithms. The proposed approach achieved accuracy scores of 0.98 , outperforming a benchmark VGG-16 model. Considerations to granular computing are given in the paper as well.

Protein phosphatase 2A (PP2A) is a ubiquitous serine/threonine phosphatase implicated in a wide variety of regulatory cellular functions. PP2A is abundant in the mammalian nervous system and dysregulation of its cellular functions are associated with myriad neurodegenerative disorders. Additionally, PP2A has oncologic implications, recently garnering attention and emerging as a therapeutic target because of the antitumor effects of a potent PP2A inhibitor, LB100. LB100 abrogation of PP2A is believed to exert its inhibitory effects on tumor progression through cellular chemo- and radio-sensitization to adjuvant agents. An updated and unifying review of PP2A biology and inhibition with LB100 as a therapeutic strategy for targeting cancers of the nervous system is needed, as other reviews have mainly covered broader applications of LB100. In this review, we discuss the role of PP2A in normal cells and tumor cells of the nervous system. Further, we summarize current evidence regarding the therapeutic potential of LB100 for treating solid tumors of the nervous system.

Background and objectives: Primary brain tumors include any tumors arising in the brain whose prognosis is poor due to their histologic characteristics. The aim of this research was to evaluate the frequency of HER2 tumor marker in primary malignant brain tumors. Materials and Methods: This descriptive study was conducted on the samples admitted to the pathology laboratory with diagnosis of primary brain tumor during 2008–2015. Results: From among 107 patients (61.7% males and the rest females) with mean age of 40.4 years, the highest frequency of tumor location was in supratentorial region of the brain (including lobes and ventricles) (63.85% cases). High-grade astrocytoma had the highest prevalence at diagnosis (43.9%), followed by low-grade astrocytoma (37.4%). As for HER2 score, 42.1% of patients were HER2-positive (scores 2 & 3). On the other hand, 5.6% of patients were HER2-negative (-), 40.2% were positive (+), and 54.2% were positive (++). The patients with high-grade astrocytoma had older age (P < 0.001), higher HER2 positivity (P = 0.024) and percentage (P < 0.001) compared to the patients with low-grade astrocytoma. Conclusions: HER2 expression is dependent on the type of brain tumors. High expression of HER2 in high-grade astrocytoma may be useful for therapeutic purposes. The future research is needed to confirm these results with a large number of patients in different areas.

Brain Tumor is one of the severe diseases and occurrence of this disease threats human life. Detection of brain tumor in advance can secure patient’s life from unwanted loss. Well-timed and swift disease detection and treatment strategy can lead to improved quality of life in these patients. This paper attempts to use Machine Learning based ensemble approaches for recognising patients with brain tumor. Ensemble technique based AdaBoost classifier and 10-fold stratified cross-validation method are assembled in single platform is proposed in this paper for prediction of brain tumor. This prediction is compared against three baseline classifiers such as Gradient Boost, Random Forest and Extra Trees classifier. Experimental result implies the superiority of this model with an accuracy of 98.97%, f1-score of 0.99, kappa statistics score of 0.95 and MSE of 0.0103.

The development of a fast and accurate intraoperative method that enables the differentiation and stratification of cancerous lesions is still a challenging problem in laboratory medicine. Therefore, it is important to find and optimize a simple and effective analytical method that enables the selection of distinctive metabolites. This study aims to assess the usefulness of solid-phase microextraction (SPME) probes as a sampling method for the lipidomic analysis of brain tumors. To this end, SPME was applied to sample brain tumors immediately after excision, followed by lipidomic analysis via liquid chromatography-high resolution mass spectrometry (LC-HRMS). The results showed that long fibers were a good option for extracting analytes from an entire lesion to obtain an average lipidomic profile. Moreover, significant differences between tumors of different histological origin were observed. In-depth investigation of the glioma samples revealed that malignancy grade and isocitrate dehydrogenase (IDH) mutation status impact the lipidomic composition of the tumor, whereas 1p/19q co-deletion did not appear to alter the lipid profile. This first on-site lipidomic analysis of intact tumors proved that chemical biopsy with SPME is a promising tool for the simple and fast extraction of lipid markers in neurooncology.

The idea of using the lytic power of viruses against the malignant cells has been entertained for many decades. However, oncolytic viruses (OV) gained broad attention as an emerging anti-cancer therapy only recently with the successful implementation of the oncolytic herpesvirus to treat advanced melanoma. OVs offer an attractive therapeutic combination of tumor-specific cell lysis together with immune stimulation, yet the latter effect is less well studied. Nevertheless, OVs can be envisaged as potential in situ tumor vaccines. The therapeutic potential of OVs can be instigated further by using the molecular biological and biotechnological tools to modify the existing viruses for their optimal tumor selectivity and enhanced immune stimulation. Furthermore, OVs can be readily combined with other therapeutic agents to increase the efficacy of the existing therapeutic schemes. In this review, we discuss biotechnological advances in the development of therapeutic applications of OVs in Russia. Particular emphasis is made on the OV-mediated treatment of glioblastoma. In addition, we highlight the challenges of oncolytic virotherapy, and describe the strategies to optimize current approaches to improve clinical outcomes.

The tumor microenvironment is known to have increased levels of cytokines and metabolites, such as glutamate, due to their release from the surrounding cells. A normal cell around the tumor that responds to the inflammatory environment is likely to be subsequently altered. We will discuss how these abnormalities will support tumor survival via the actions of gap junctions (GJs) and hemichannels (HCs) which are composed of hexamer of connexin 43 (Cx43) protein. In particular, we will discuss how GJ intercellular communication (GJIC) in glioma cells, the primary brain tumor, is a regulatory factor and its attenuation leads to tumor invasion. In contrast, the astrocytes, which are normal cells around the glioma, are "hijacked" by tumor cells, either by receiving the transmission of malignant substances from the cancer cells via GJIC, or perhaps via astrocytic HC activity through the paracrine signaling which enable the delivery of these substances to the distal astrocytes. This astrocytic signaling would promote tumor expansion in the brain. In addition, brain metastasis from peripheral tissues has also been known to be facilitated by GJs formed between cerebral vascular endothelial cells and cancer cells. Astrocytes and microglia are generally thought to eliminate cancer cells at the blood brain barrier. In contrast, some reports suggest they facilitate tumor progression as tumor cells take advantage of the normal functions of astrocytes that support the survival of the neurons by exchanging nutrients and metabolites. In summary, GJIC is essential for the normal physiological function of growth and allowing the diffusion of physiological substances. Therefore, whether GJIC is cancer promoting or suppressing may be dependent by what permeates through GJs, when it is active, and to which cells. The nature of GJs, which has been ambiguous in brain tumor progression, will need to be re-visited and understood together with new findings on Cx proteins and HC activities.

Brain tumors are abnormal cells growth in the brain tissues that can be cancerous, or not. In any case, they could be a very aggressive disease that should be detected as early as possible. Usually, magnetic resonance imaging (MRI) is the main tool commonly adopted by neurologists and radiologists to identify and classify any possible anomalies present in the brain anatomy. In the present work, an automatic unsupervised method called Z2-$\gamma$, based on the use of adaptive finite-elements and suitable pre-processing and post-processing techniques, is introduced. In particular, the proposed methodology is able to automatically classify whether a given MR image represents a healthy or a diseased brain and in this latter case, is able to locate the tumor area.

Segmentation of brain tumor images is a major research topic in medical imaging to have a refined detection and understanding of abnormal masses in the brain. This paper proposes a new segmentation method, consisting of three main steps, to detect brain lesions using magnetic resonance imaging (MRI). In the first step, the parts of the image delineating the skull bone are removed to exclude insignificant data. In the second step, which is the main contribution of this study, the particle swarm optimization (PSO) technique is applied to detect the block that contains the brain lesions. The fitness function, used to determine the best block among all candidate blocks, is based on a two-way fixed-effects analysis of variance (ANOVA). In the last step of the algorithm, the K-means segmentation method is used in the lesion block to classify it as tumor or not. A thorough evaluation of the proposed algorithm is performed using the MRI database provided by the Kouba imaging center in Algiers, Algeria. Estimates of the selected fitness function are first compared to those based on the sum-of-absolute-differences (SAD) dissimilarity criterion and demonstrate the efficiency and robustness of the ANOVA. The performance of the optimized brain tumor segmentation algorithm is then compared to the results of several state-of-the-art techniques, including fuzzy C-means, K-means, Otsu thresholding, local thresholding, and watershed segmentation. The results obtained using Dice coefficient, Jaccard distance, correlation coefficient, and root mean square error (RMSE) measurements demonstrate the superiority of the proposed optimized segmentation algorithm over equivalent techniques.

Extensive growth in the volume of irregular brain cells is known as brain tumor. Human brain is surrounded by stiff skull. There are various issues that occur due to the growth of any tumor inside this restricted space. The malignant and benign are two main categories of the brain tumor. The skull is pressurized to enlarge from inside in case of growth of any benign or malignant tumor. This tumor leads to harm in brain and it may be dangerous to life also. The brain tumor is divided into two kinds - primary or secondary. The brain tumor detection techniques have various phases. In this paper, comparative study of CNN with GLCM approach and superpixel based spectral clustering is done tumor. This work takes into account metrics like accuracy, sensitivity and specificity for drawing the comparison between both the techniques.

Deep learning has shown remarkable results in every field, especially in the biomedical field, due to its ability to exploit large-scale datasets. A convolutional neural network (CNN) is a widely used deep learning approach to solve medical imaging problems. Over the past few years, many studies have focused on CNN-based techniques for brain tumor diagnosis. There are, however, still some critical challenges that CNNs face towards clinic application. This study presents a comprehensive review of current literature that involves CNN architectures for brain tumor classification. We compare the key achievements in the performance evaluation metrics of the applied classification algorithms. In addition, this review assesses the clinical effectiveness of the included studies to elaborate on the limitations and directions of this area for future work. No review focusing on the clinical effectiveness of previous works in this field has been published. We believe that this study has the potential to elevate the application of CNN-based deep learning methods in clinical practice and also can be a quick reference for biomedical researchers who are interested in this field.

Abstract: Tumor-targeting and blood-brain barrier (BBB)-penetrating are highly desirable for the treatment of glioma. In this study, we developed Pep-1&borneol-bifunctionalized carmustin-loaded micelles (Pep-1/Bor/CMS-M) capable of targeting to IL-13 receptor-overexpressed glioma and penetrating the brain microvascular endothelial cells-associated physiologic barriers. Pep-1/Bor/CMS-M were nearly spherical particles with a dimeter of 32.6 ± 1.1 nm and zeta potential of -21.3 ± 3.1 mV. Carmustine (CMS) released from Pep-1/Bor/CMS-M in pH 7.4 was significantly faster than in acidic environments. In human glioma BT325 cellular studies, Pep-1/Bor/CMS-M remarkably increased the cytotoxicity, notably improved the internalization and effectively induced the cell apoptosis. Likewise, in human brain microvascular endothelial cells (HBMEC) cells, Pep-1/Bor/CMS-M obviously promoted the cellular uptake, rapidly decreased the transepithelial electrical resistance (TEER) and thereby of enhancing the ability of penetration. In orthotopic Luc-BT325 glioma tumor-bearing nude mouse models, the stronger fluorescence signal and longer retention were observed in brain tissues compared with other controls, after single administration of DiD-labelled Pep-1/Bor/M (DiD/Pep-1/Bor/M). Importantly, Pep-1/Bor/CMS-M displayed the strongest inhibition of tumor growth, the longest survival period and low systemic toxicity in treating orthotopic glioma tumor-bearing nude mice. Simultaneous functionalization of Pep-1 and borneol offers a novel strategy for designing CMS-based nanomedicine and precisely treating glioma.

Natural killer (NK) cell therapy is one of the most promising treatments for Glioblastoma Multiforme (GBM). However, this emerging technology is limited by the availability of sufficient numbers of fully functional cells. Here, we investigated the efficacy of NK cells that were expanded and treated by interleukin-2 (IL-2) and heat shock protein70 (HSP70), both in vitro and in vivo. Proliferation and cytotoxicity assays were used to assess the functionality of NK cells in vitro, after which treated and naïve NK cells were administrated intra-cranially and systemically to compare the potential antitumor activities in our in vivo rat GBM models. In vitro assays provided strong evidence of NK cell efficacy against C6 tumor cells. In vivo tracking of NK cells showed efficient homing around and within the tumor site. Furthermore, significant amelioration of the tumor in rats treated with HSP70/Il-2 treated NK cells as compared to those subjected to non-treated NK cells, as confirmed by MRI, proved the efficacy of adoptive NK cell therapy. Moreover, results obtained with systemic injection confirmed migration of activated NK cells over the blood brain barrier and subsequent targeting of GBM tumor cells. Our data suggest that administration of HSP70/Il-2 treated NK cells may be a promising therapeutic approach to be considered in the treatment of GBM.

Along just over a century of research we moved from learning how to cultivate tissues in a dish to grasping the concepts for creating an entire brain in a vat. As we approach the divisive moment in which we can first detect signs of awareness in such artificially developed organoids, we need to lay foundation for what lays ahead. It is crucial that ethical, legal and moral implications of organoid research are clear and that boundaries are set to separate scientific progress from human life preservation. The largest obstacle may be the definition of consciousness itself, which has arguably been historically neglected by philosophy, psychology and neurosciences at large. One reason may be the difficulties posed by the underlying qualities of awareness, such as its subjective and heterogeneous nature. Another reason may lie on the possibly that consciousness is an overarching emergent property of our brain. For the time being, one can see brain organoids as philosophical zombies, physical analogues of the human brain which mimic sentient human reactions but lack experiential properties of sensation (a.k.a. qualia).

Background: There is an increasing interest in the role of EEG in neurorehabilitation. We primarily aimed to identify the knowledge base through highly influential studies. Our secondary aims were to imprint the relevant thematic hotspots, research trends, and social networks within the scientific community. Methods: We performed an electronic search in Scopus looking for studies reporting on rehabilitation in patients with neurological disabilities. The most influential papers outlined the knowledge base, while a word co-occurrence analysis imprinted the research hotspots. Likewise, co-citation analyses highlighted collaboration networks between Universities, authors, and countries. The results were presented in summary tables, burst detection plots, and geospatial maps. Finally, a content review based on the top-20 most cited articles completed our study. Results: Our current bibliometric study was based on 874 records from 420 sources. There was a vivid research interest in EEG use for neurorehabilitation, with an annual growth rate as high as 14.3%. The most influential paper was the study titled "Brain-computer interfaces, a review" by Nicolas-Alfonso LF and Gomez-Gill J, with 997 citations, followed by "Brain-computer interfaces in neurological rehabilitation" by Daly J. and Wolpaw JR (708 citations). The USA, Italy, and Germany were among the most productive countries. The research hotspots shifted with time from the use of “functional magnetic imaging” to EEG-based “brain-machine interface”, “motor imagery”, and “deep learning”. Conclusions: EEG constitutes the most significant input in brain-computer interfaces (BCI) and can be successfully used in the neurorehabilitation of patients with stroke, amyotrophic lateral sclerosis, and traumatic brain and spinal injury. EEG-based BCI facilitates training, communication, and control of wheelchair and exoskeletons. However, research is limited to specific scientific groups from developed countries. Evidence is expected to change with the broader availability of BCI and improvement in EEG filtering algorithms.

Recent progress in microfabrication technique allowed the rapid development of neural implants. They are getting categorized as effective tools for clinical practice, especially to treat traumatic and neurodegenerative disorders. Microelectrode arrays already have been used in numerous neural interface devices. Basically, almost all neural implants have been developed based on BCI (Brain Computer Interface) system. When BCI system falls under invasive technique, it is referred as BMI or Brain Machine Interface. BMIs hold promises for neurorehabilitation of motor and sensory function, cognitive state evaluation and treatment of neurological chaos. A directed overview of the field of neural implants is discussed in this article. The aim of this review is to give a brief introduction of neural prosthetics as well as their exciting applications in treating neurological disorders and a deep discussion on their functionality are mentioned. BCI system and their different types, their functionality, their pros and cons, how other neural implants developed, and their present status have been covered. Different possibilities and possible future of deep brain stimulation (DBS), Neuralink, motor and sensory neural prosthetics are further discussed.

Tissues of the brain, especially white matter, are extremely heterogeneous - with constitutive response varying spatially. In this paper, we implement a high-resolution Finite Element (FE) head model where heterogeneities of white matter structures are introduced through Magnetic Resonance Elastography (MRE) experiments. Displacement of white matter under shear wave excitation is captured and the material properties determined though an inversion algorithm are directly used in the FE model. This approach is found to improve model predictions when compared to experimental results. In the first place, responses in the cerebrum near stiff structures such as the corpus callosum and corona radiata are markedly different compared with a homogenized material model. Additionally, the heterogeneities introduce additional attenuation of the shear wave due to wave scattering within the cerebrum.

One of the biggest queries in cognitive sciences is the emergence of consciousness from matter. Modern neurobiological theories of consciousness propose that conscious experience is the result of interactions between large-scale neuronal networks in the brain, traditionally described within the realm of classical physics. Here, we propose a generalized connectionist framework in which the emergence of “conscious networks” is not exclusive of large brain areas, but can be identified in sub-cellular networks exhibiting non-trivial quantum phenomena. The essential feature of such networks is the existence of strong correlations in the system (classical or quantum coherence) and the presence of an optimal point at which the system’s complexity is maximized, expressed either by maximization of the information content in large scale functional networks or by achieving optimal efficiency through the quantum Goldilock effect.

Magnetic Nanoparticles (MNPs) is a promising technique to cure brain diseases. On the one hand, by serving as drug carriers, they can bypass the blood-brain barrier and deliver drug molecules to the brain parenchyma; on the other hand, their transport trajectory can be manipulated by applying an external magnetic field. However, due to the complex microstructure of brain tissues, e.g. the anisotropy of white matter (WM), how to achieve desired drug distribution patterns, e.g. uniform distribution, by tuning the drug delivery system is largely unknown. Here, in this study, by adopting a mathematical model capable of capturing the diffusion trajectories of MNPs in the microstructures, we systematically investigated the effects of key parameters in the MNPs delivery system on the equivalent diffusion coefficient of MNPs in the microenvironment of brain WM. The results show that uniform distribution of MNPs in anisotropic tissues can be achieved by adjusting the particle size and magnetic field. We have not only obtained a deeper understanding on how to optimise the MNPs delivery system, it can also be anticipated that an improved mathematical model could even help to achieve complex drug distribution patterns in the complicated brain environment by designing an appropriate combination of the key parameters.

Proper nutrition is crucial for normal brain and neurocognitive development. Failure to optimize neurodevelopment early in life can have profound long-term implications for both mental health and quality of life. Although the first 1000 days of life represent the most critical period of neurodevelopment, the central and peripheral nervous systems continue to develop and change throughout life. All this time, development and functioning depend on many factors, including adequate nutrition. In this review, we outline the role of nutrients in cognitive, emotional, and neural development in infants and young children with special attention to the emerging roles of polar lipids and high quality (available) protein. Furthermore, we discuss the dynamic nature of the gut-brain axis and the importance of microbial diversity in relation to a variety of outcomes, including brain maturation/function and behavior are discussed. Finally, the promising therapeutic potential of psychobiotics to modify gut microbial ecology in order to improve mental well-being is presented. Here we show that the individual contribution of nutrients, their interaction with other micro-and macronutrients, and the way in which they are organized in the food matrix are of crucial importance for normal neurocognitive development.

Our knowledge on the plastic functions of the serotonin (5-HT) receptor subtype 7 (5-HT7R) in the brain physiology and pathology considerably advanced in the last few years. A wealth of data show that the 5-HT7R is a key player in the establishment and remodeling of neuronal cytoarchitecture during development and in the mature brain, and its dysfunction is linked to neuropsychiatric and neurodevelopmental diseases. The involvement of this receptor in synaptic plasticity is further demonstrated by data showing that its activation allows to rescue long term potentiation (LTP) and long term depression (LTD) deficits in various animal models of neurodevelopmental diseases. In addition, it is becoming clear that the 5-HT7R is involved in inflammatory intestinal diseases, possibly playing a role in the gut-brain axis, and modulates the function of immune cells. In this review, we will mainly focus on recent findings on this receptor’s role in the structural and synaptic plasticity of the mammalian brain, although we will also illustrate novel aspects highlighted in gut and immune system.

Here, we review findings and trends in sleep research in 2020-2021 demonstrating how COVID-19 and sleep disorders can induce the BBB leakage via neuroinflammation, which might contribute to the 'coronasomnia' phenomenon. The new studies suggest that the controlling of sleep hygiene and quality should be incorporated into the rehabilitation of COVID-19 patients. We also discuss perspective strategies for prevention of COVID-19-related BBB disorders. We demonstrate that sleep might be a novel biomarker of the BBB leakage and the analysis of sleep EEG patterns can be a breakthrough non-invasive technology for diagnosis of the COVID-19-caused BBB disruption.

New research points to a possible link between Autism Spectrum Disorder and the gut microbiota as many autistic children have co-occurring gastrointestinal problems. This review focuses on specific alterations of gut microbiota mostly observed in autistic patients. Particularly, the mechanisms through which such alterations may trigger the production of the bacterial metabolites or leaky gut in autistic people are described. Various altered metabolite levels were observed in autistic children, many of those were of bacterial origin such as short chain fatty acids (SCFAs), indoles and lipopolysaccharides. A less integrative gut-blood-barrier is abundant in autistic individuals. This explains the leakage of bacterial metabolites into the patients triggering new body responses or altered metabolism. Some other co-occurring symptoms such as mitochondrial dysfunction, oxidative stress in the cells, altered tight junctions in the blood brain barrier and structural changes in cortex, hippocampus, amygdala and cerebellum were detected. Moreover, this paper suggests that autism is associated with an unbalanced gut microbiota (dysbiosis). Although the cause-effect relationship between autism and gut microbiota is not yet well established, consumption of specific probiotics may represent a powerful tool to re-establish gut homeostasis and promote gut health. Diagnostic and therapeutic value of new biomarkers leading to the perturbation in the phenylalanine metabolism will be discussed.

A facilitative transport system exists on the blood brain barrier (BBB) that has been tacitly assumed to be a path for glutamate entry to brain. But glutamate is a non-essential amino acid whose brain content is much greater than plasma, and studies in vivo show that glutamate does not enter brain in material quantities except in those small regions with fenestrated capillaries (circumventricular organs). The situation became understandable when luminal (blood facing) and abluminal (brain facing) membranes were isolated and studied separately. Facilitative transport of glutamate and glutamine exist only on the luminal membranes whereas Na+-dependent transport systems for glutamate, glutamine and some other amino acids are present only on the abluminal membrane. The Na+-dependent cotransporters of the abluminal membrane are in a position to actively transport amino acids from the extracellular fluid (ECF) into the endothelial cells of the BBB. These powerful secondary active transporters couple the energy of the Na+-gradient to move glutamate and glutamine into the ECF whereupon glutamate can exit to blood on the luminal facilitative glutamate transporter. Glutamine may also exit brain on a separate facilitative transport system that exists on the luminal membranes or glutamine can be hydrolyzed to glutamate within the BBB thereby releasing ammonia that is freely diffusible. The γ-glutamyl participate cycle participates indirectly by producing oxoproline (pyroglutamate) that stimulates almost all secondary active transporters yet discovered in the abluminal membranes of the BBB.

We introduce a mission design for an interstellar expedition to nearby earth-like exoplanets, which our analysis determined to be Tau Ceti and Gliese 667C, at the time of analysis in 2013. We review the research problems in propulsion and AGI that must be addressed to launch an AI guided interstellar probe within 100 years. We propose a new semi-autonomous agent approach for intelligent control of the spacecraft. We introduce the concept of a semi-autonomous agent as having built-in safety guarantees that constrain operation. An autonomous agent case study is presented formulating the objective, constraints, AGI implementation of the agent based on Solomono's Alpha architecture, and adding specicity. We discuss the training required to reach human-level and trans-sapient levels of intelligence which corresponds to an entire crew of AI experts specialized in elds such as astrophysics, astromechanics, astrobiology, quantum physics, computer science, molecular biology, and so forth. We project the feasibility of the human-level AI technology based on empirical ndings in neuroscience, and nd that it should be feasible by 2030. We analyze Solomono's innity point hypothesis in light of Koomey's law about energy eciency of computing and nd that the trends in 2013 indicated an early singularity by 2035, which implies that we might encounter physical bottlenecks which will decelerate computing technology improvements signicantly. We recommend thus year 2040 for launching the probe by which date other required technologies will have been developed. We discuss the scenario of a virtual crew made of brain simulations, which is a bio-information based AI approach. We detail the subsystems of command and control, communication, scientic instrumentation, power, propulsion, navigation, and shielding. We propose a variation of ICAN-II/AIMStar propulsion which uses a positron source instead of anti-protons to initiate micro-fusion reactions. We combine the positron initiated fusion pulse propulsion scheme with a miniaturized version of the Daedelus fusion thruster obtaining high performance. We derive two mission proles one for fusion pulse propulsion, and the yet hypothetical Q-Thruster. Fusion thruster requires 132.2 years for Tau Ceti, and 233.2 years for Gliese 667C, while Q-Thruster takes only 42.3 years for Tau Ceti, and 62.5 years for Gliese 667C. We also discuss extended roles for intelligent interstellar probes such as self-reproduction via nanotechnology, refueling, construction, robotic bodies, and transmission of brain simulations.

There is evidence that spaceflight poses acute and late risks on the central nervous system. To explore possible mechanisms, the proteomic changes following spaceflight in mouse brain were characterized. Space Shuttle Atlantis (STS-135) was launched at the Kennedy Space Center on a 13-day mission. Within 3–5 hours after landing, brain tissue was collected to evaluate protein expression profiles using quantitative proteomic analysis. Our results showed that there were 26 proteins that were significantly altered after spaceflight in the grey and/or white matter. While there was no overlap between the white and grey matter in terms of individual proteins, there was overlap in terms of function, synaptic plasticity, vesical activity, protein/organelle transport, and metabolism. Our data demonstrate that exposure to the spaceflight environment induces significant changes in protein expression related to neuronal structure and metabolic function. This might lead to a significant impact on brain structural and functional integrity that could affect the outcome of space missions.

Malignant gliomas are the most common primary brain tumors in adults up to an extent of 78% of all primary malignant brain tumors. However, total surgical resection is almost unachievable due to considerable infiltrative ability of glial cells. The efficacy of current multimodal therapeutic strategies is, furthermore, limited by the lack of specific therapies against malignant cells, and, therefore, the prognosis these in patients is still very unfavorable. The limitation of conventional therapies, which may result from inefficient delivery of the therapeutic or contrast agent to brain tumors are major reasons for this unsolved clinical problem. The major problem in brain drug delivery is the presence of the blood brain barrier which limits the delivery of many chemotherapeutic agents. Nanoparticles, thanks to their chemical configuration, are able to go through the blood-brain barrier carrying drugs or genes targeted against gliomas. Carbon nanomaterials show distinct properties including electronic properties, penetrating capability on the cell membrane, high drug-loading and pH-dependent therapeutic unloading capacities, thermal properties, large surface area and easy modification with molecules, which render them as a suitable candidate to deliver drugs. In this review we will focus on the potential effectiveness of the use of carbon nanomaterials in the treatment of malignant gliomas discussing the current progress of in vitro and in vivo researches of carbon nanomaterials-based drug delivery to brain.

Head injury is among the most devastating types of injury, specifically called Traumatic Brain Injury (TBI). There is need to diminish the morbidity related with TBI and to improve the outcome of patients suffering TBI. Among the improvements on the treatment of TBI, neuroprotection is one of the upcoming improvements. Citicoline has been used in the management of brain ischemia related disorders, such as TBI. Citicoline has biochemical, pharmacological, and pharmacokinetic characteristics that make it a potentially useful neuroprotective drug for the management of TBI. A short review of these characteristics is included in this paper. Also, a narrative review of almost all the published or communicated studies performed with this drug in the management of patients with head injury is included. Based on the results obtained in these clinical studies, it is possible to conclude that citicoline was able to accelerate recovery of consciousness and to improve the outcome of this kind of patients, with an excellent safety profile. Thus, citicoline could have a potential role in the management of TBI.

Current hypotheses implicate insulin resistance of the brain as a pathogenic factor in the development of Alzheimer’s disease and other dementias, Parkinson’s disease, type 2 diabetes, obesity, major depression, and traumatic brain injury. A variety of genetic, developmental, and metabolic abnormalities that lead to disturbances in the insulin receptor signal transduction may underlie insulin resistance. Insulin receptor substrate proteins are generally considered to be the node in the insulin signaling system that is critically involved in the development of insulin insensitivity during metabolic stress, hyperinsulinemia, and inflammation. Emerging evidence suggests that lower activation of the insulin receptor (IR) is another common, while less discussed, mechanism of insulin resistance in the brain. This review aims to discuss causes behind the diminished activation of IR in neurons, with a focus on the functional relationship between mitochondria and IR during early insulin signaling and the related roles of oxidative stress, mitochondrial hypometabolism, and glutamate excitotoxicity in the development of IR insensitivity to insulin.

Current hypotheses implicate insulin resistance of the brain as a pathogenic factor in the development of Alzheimer’s disease and other dementias, Parkinson’s disease, type 2 diabetes, obesity, major depression, and traumatic brain injury. A variety of genetic, developmental, and metabolic abnormalities that lead to disturbances in the insulin receptor signal transduction may underlie insulin resistance. Insulin receptor substrate proteins are generally considered to be the node in the insulin signaling system that is critically involved in the development of insulin insensitivity during metabolic stress, hyperinsulinemia, and inflammation. Emerging evidence suggests that lower activation of the insulin receptor (IR) is another common, while less discussed, mechanism of insulin resistance in the brain. This review aims to discuss causes behind the diminished activation of IR in neurons, with a focus on the functional relationship between mitochondria and IR during early insulin signaling and the related roles of oxidative stress, mitochondrial hypometabolism, and glutamate excitotoxicity in the development of IR insensitivity to insulin.

Stereotactic radiosurgery (SRS) has become increasingly important in the management of brain metastases due to improving systemic disease control and rising incidence. Initial trials demonstrated SRS with whole brain radiotherapy (WBRT) improved local control rates versus WBRT alone. Concerns with WBRT associated neurocognitive toxicity have contributed to greater use of SRS alone, including for patients with multiple metastases and following surgical resection. Molecular information, targeted agents and immunotherapy have also altered the landscape for the management of brain metastases. This review summarises current and emerging data on the role of SRS in the management of brain metastases.

During the 90 days following hospitalization for acute heart failure, ejection fraction and type of discharge medications have been shown in clinical trials to have little effect on mortality. We examined the recent literature addressing brain-related etiologies of sudden death following heart failure. Two mechanisms of sudden unexpected death have been suggested to possibly result from 4 significant influences on pathophysiology in the brain. The two causes of death are severe cardiac arrhythmia, and neurogenic pulmonary edema. They are both mediated through the brainstem autonomic nuclei generally, and executed specifically through the dorsal motor nucleus of the vagus nerve. The four significant influences on pathophysiology in the brainstem autonomic nuclei are: 1) Hyper-stimulation of neurons in the solitary tract nucleus, increasing their metabolic requirements; 2) Inadequate blood flow at a vascular watershed terminus; 3) Additionally decreased blood flow following vasoconstriction related to relative hyperventilation and decreased pCO2 levels; 4) Gravitational ischemia in the brain—caused by the weight of the brain mass sitting above the brainstem. Changes in head tilt release gravitational ischemia in the brain. There is no specific head position (relative to gravity) that is considered favorable or unfavorable for an extended period of time (i.e. more than 24 hours). Even a small degree of head elevation, used in managing pulmonary congestion, may increase gravitational ischemia in the posterior fossa and brainstem. In this paper we suggest a new and important research avenue for intervening in cardiac arrhythmias, and preventing their occurrence, through the non-invasive use of head-tilting, and other head repositioning maneuvers. This could potentially help many geriatric patients with heart failure, who have decreased mobility in bed, and who tend to stay in one position longer, thereby increasing gravitational ischemia in the brain.

Glioblastoma (GBM) is the most common primitive tumor in adult central nervous system (CNS), classified as grade IV according to WHO 2016 classification. GBM shows a poor prognosis with an average survival of approximately 15 months, representing an extreme therapeutic challenge. One of its distinctive and aggressive features is aberrant angiogenesis, which drives tumor neovascularization, representing a promising candidate for molecular target therapy. Although several pre-clinical studies and clinical trials have shown promising results, anti-angiogenic drugs have not led to a significant improvement in overall survival (OS), suggesting the necessity of identifying novel therapeutic strategies. Metformin, an anti-hyperglycemic drug of the Biguanides family, used as first line treatment in Type 2 Diabetes Mellitus (T2DM), demonstrated in vitro and in vivo antitumoral efficacy in many different tumors, including GBM. From this evidence, a process of repurposing of the drug has begun, leading to the demonstration of the inhibition of various oncopromoter mechanisms and, consequently, to the identification of the molecular pathways involved. Here, we review and discuss the potential metformin’s antitumoral effects on GBM, inspecting if it could properly act as an anti-angiogenic compound to be considered as a safely add-on therapy in the treatment and management of GBM patients.

In recent years, pathoconnectomics emerged as an interesting framework for the investigation and better comprehension of disorders affecting the brain. Research in this field has used so far structural, functional, metabolic and genetic data, but limited attention was addressed to the possible role of vascularization. In the present work the following aspects making it a valuable candidate to pathoconnectomics investigation are discussed: i) The vascular system is by its nature a network, endowed with directionality information on the basis of circulation; ii) The current imaging techniques allow in vivo detection of the vascular system to a good level of detail; iii) The information extracted from this kind of data could interact in a meaningful way with the functional profile of the brain, being the BOLD effect in turn based on blood flow; iv) Further evidence could be found in support of the trophic failure hypothesis; v) Data about vascularization could allow to bring in the pathoconnectomics framework cardiovascular and metabolic disorders. We suggest, therefore, that the evaluation of vascular connectivity (which we propose to name “vesselomics”) could enhance the pathoconnectomics paradigm, and provide new elements towards the understanding of brain pathology.

Since matter, energy and information are the three major components of the world, is there an interaction between information and matter? In the present work, the coevolution of human language and brain is taken as a case of interaction between information and brain. Some evidence that may show interactions between human language and brain revealed by previous researches is summarized in this paper, such as the language areas in the cerebral cortex of the modern human brain, the evolution of human language and brain in human history, and the genetic basis for the evolution of language. Based on the evidence, a dynamic model is developed to investigate the possible mechanism of coevolution of human language and brain. In the model, human language development and brain development reinforce each other: the developmental level of language can be promoted by advances in brain function due to language-related gene mutations, in turn, whether such mutations are selected positively can be influenced by the current developmental level of language. The coevolution of human language and brain can be taken as a case of interaction between information and matter.

In this article, we posit an approach to study brain processesnby means of the quantum-classical dynamics of a Mixed Weyl symbol. The Mixed Weyl symbol is used to describe brain processes at the microscopic level and, when averaged over an appropriate ensemble, provides a link to the results of measurements made at the mesoscopic scale. The approach incorporates features of three well-known approaches (which are also reviewed in this paper), namely the electromagnetic field theory of the brain, orchestrated objective reduction theory, and the dissipative quantum model of the brain. Within this approach, quantum variables (such as nuclear and electron spins, dipolar particles, electron excited states, and tunnelling degrees of freedom) may be represented by spinors while the electromagnetic fields and phonon modes involved in the processes are treated either classically or semiclassicaly, by also considering quantum zero-point fluctuations. In the proposed computation scheme, zero-point quantum effects can be incorporated into numerical simulations by controlling the temperature of each field mode via coupling to a dedicated Nosè-Hoover chain thermostat. The temperature of each thermostat is chosen in order to reproduce quantum statistics in the canonical ensemble. Viewing the brain in terms of QC processes has consequences on the theory of clinical psychology and potential implications for its practice.

The advancement of the pediatric traumatic brain injury (TBI) knowledge base requires biospecimens and data from large samples. This study seeks to describe a novel clinical research modality to establish best practices for enrolling a diverse pediatric TBI population and quantifying key information on enrollment into biobanks. Screening form responses were standardized and cleaned through Google Sheets. Data was used to analyze total individuals at each enrollment stage. R was utilized for final analysis, including chi-square goodness of fit and proportion statistical tests, to determine further significance and relationships. Issues throughout data cleaning shed light on limitations of the consent modality. Results suggest that through a diverse research team, the recruited sample exceeds traditional measures of representation (e.g. sex, race, ethnicity). Sex demographics of the study are representative of the local population. Screening for candidates is critical to the success of the consent modality. The consent modality may be modified to increase diversity of study population and accept bilingual candidates. Researchers must implement best practices, including increasing inclusivity of bilingual populations, utilizing technology, and improving participant follow-up, to improve health disparities for understudied clinical populations.

Machine Learning (ML) approaches have been fruitfully applied to several classification problems of neurophysiological activity. Considering the relevance of emotion in human cognition and behaviour, ML found an important application field in emotion identification based on neurophysiological activity. Nonetheless, the literature results present a high variability depending on the neuronal activity measurement, the signal features and the classifier type. The present work aims to provide new methodological insight on ML applied to emotion identification based on electrophysiological brain activity. For this reason, we recorded EEG activity while emotional stimuli, high and low arousal (auditory and visual) were provided to a group of healthy participants. Our target signal to classify was the pre-stimulus onset brain activity. Classification performance of three different classifiers (LDA, SVM and kNN) was compared using both spectral and temporal features. Furthermore, we also contrasted the classifiers performance with static and dynamic (time evolving) features. The results show a clear increased in classification accuracy with temporal dynamic features. In particular, the SVM classifiers with temporal features showed the best accuracy (63.8 %) in classifying high vs. low arousal auditory stimuli.

The basal ganglia (BG) are a central component of the brain, crucial to the initiation, execution and learning of adaptive actions. The BG are the major site of the action of dopamine. An important aspect of the BG architecture is the existence of two paths, direct and indirect, having different projection targets and dopamine receptor expression. To understand the BG, dopamine, and related disorders, it is imperative to understand the two paths. The standard account used in neuroscience research for decades posits that the role of the direct path is to support movements, while that of the indirect path is to suppress unselected or completed movements. This account is contradicted by converging evidence. Here, we explain why the arguments supporting the standard account are flawed, and present a new account, in which the role of the indirect path is completely opposite: to support automated execution. During acute events, the direct path allows coarse responses. These are refined by competition, and the resulting focused response is executed and learned by the indirect path, assisted by cholinergic interneurons and the subthalamic nucleus (STN). The new account allows a novel understanding of the symptoms of Parkinson's disease, in particular tremor and rigidity, and of its treatment by STN deep brain stimulation.

The paper presents a study of two novel visual motion onset stimulus-based brain–computer interfaces (vmoBCI). Two settings are compared with afferent and efferent to a computer screen center motion patterns. Online vmoBCI experiments are conducted in an oddball event–related potential (ERP) paradigm allowing for “aha–responses” decoding in EEG brainwaves. A subsequent stepwise linear discriminant analysis classification (swLDA) classification accuracy comparison is discussed based on two inter–stimulus–interval (ISI) settings of 700 and 150 ms in two online vmoBCI applications with six and eight command settings. A research hypothesis of classification accuracy non–significant differences with various ISIs is confirmed based on the two settings of 700 ms and 150 ms, as well as with various numbers of ERP response averaging scenarios.The efferent in respect to display center visual motion patterns allowed for a faster interfacing and thus they are recommended as more suitable for the no–eye–movements requiring visual BCIs.

A chronic activated pro-inflammatory cytokine network (“inflamm-aging”) may amplify the neurodegenerative effects of a fall induced brain trauma in geriatric subjects. Our research aimed to evaluate how a trained machine learning algorithm may predict recent antecedent falls based only on specific serologic cytokines network analysis and how the consequences of these falls can be substantiated on standard head MRIs. All 279 subjects included in our study were selected from the ADNI1 dataset and all had a mild cognitive impairment diagnostic at the ADNI1 study baseline. A “train group” was built and included 14 subjects with a history of a recent, simple, standing-level fall. These were carefully matched with 14 similar subjects without any antecedent trauma. The “test group” included 251 subjects, all without any history of recent fall. The machine learning algorithm (classic C4.5 decision tree) was trained to detect a pattern of variation in 23 clinically relevant cytokines in relation with an antecedent fall. Changes in five cytokines (matrix metalloproteinase-7, eotaxin-1, interleukin-3, interleukin-8 and matrix metalloproteinase-9) were used for fall prediction in the “test” group. Once trained, the algorithm predicted a recent fall in 119 cases from the test group. The mean brain ventricular volume that was significantly different between fall/non-fall subgroups (41645.5±10337.2 vs 27127.3±6749.4 mm3, p=0.005) remained significant in the test group, after prediction between (41544.24±17343.4 vs 34553.5±10543.2 mm3, p=0.042). The hippocampus mean volume was also significantly different between in the test group (6297.3±1080.1 vs 6745.9±1123.7, p=0.0015). A significant brain ventricular difference was observed in the “65<y.o.” subgroup (p=0.04). If confirmed by larger prospective studies, our findings may increase the precision of the neuro-cognitive assessments in geriatric subjects.

Background: The vegetative state (VS)/unresponsive wakefulness syndrome (UWS) denotes brain-injured, awake patients who are seemingly without awareness. Still, up to 15% of these patients show signs of covert consciousness when examined by functional magnetic resonance imaging (fMRI) or EEG, which is known as cognitive motor dissociation (CMD). Most experts prefer the term unresponsive wakefulness syndrome to avoid the negative connotations associated with vegetative state and to highlight the possibility for CMD. However, the perception of VS/UWS by the public has never been studied systematically. Methods: Using an online crowdsourcing platform, we recruited 1297 participants from 32 countries. We investigated if vegetative state and unresponsive wakefulness syndrome might have a different influence on attitudes towards VS/UWS and CMD. Results: Participants randomized to be inquired about the vegetative state believed that CMD was less common (mean estimated frequency in unresponsive patients 38.07% ± SD 25.15) than participants randomized to unresponsive wakefulness syndrome (42.29% ± SD 26.63; p=0.016). Attitudes towards treatment withdrawal were similar. Most participants preferred unresponsive wakefulness syndrome (60.05%), although a sizeable minority favored vegetative state (24.21%; difference 35.84%, 95% CI 29.36 to 41.87; p<0.0001). Searches on PubMed and Google Trends revealed that unresponsive wakefulness syndrome is increasingly used by academics but not lay people.Discussion: Simply replacing vegetative state with unresponsive wakefulness syndrome may not be fully appropriate given that 1 of 4 prefer the first term. We suggest that physicians take advantage of the controversy around the terminology to explain relatives the concept of CMD and its ethical implications.

Sports traumatic brain injury (TBI) accounts for up to 20% of all sports injuries, and the number of cases is growing year by year due to an increase in the number of people involved in sports, the growing popularity of extreme and contact sports, as well as a high level of motivation to achieve record results. Mild TBI dominates, which can provoke the development of a very wide range of complications and negative consequences. In the programs for the prevention of complications and the rehabilitation of athletes after TBI, TBI features are not sufficiently considered, which significantly differ from household, road or criminal injuries. There are no instrumental methods for diagnosing the severity of the injury. Sports TBI is characterized by repeated frequent TBI, elevated body and brain temperature, peripheral redistribution of blood flow and hypocapnia, which significantly affect cerebral blood flow. Brain injury is an independent cause of the development of cerebral hyperthermia, which significantly worsens the consequences of TBI. To diagnose sports TBI, the method of microwave radiometry of the brain (MWR) can be used. For the prevention of complications, the technology of craniocerebral hypothermia (CCH), which allows for to reduce of physical general and cerebral hyperthermia, and increases the resistance of cerebral cortex neurons to hypoxia and trauma could be used However, these approaches in sports medicine are used sporadically, which, is due to the lack of awareness of coaches and doctors of sports teams. The purpose of the review is to present MWR and CCH in sports TBI.

Background: Cognitive-behavioral alterations can occur after an acquired brain injury. It is a stressful situa-tion for patient and relatives. Objectives: To develop and evaluate a synchronous online training program on emotional intelligence (EI) for caregivers of adult patients with cognitive-behavioral impairment due to acquired brain injury. Methods: A quasi-experimental study was designed, a target population of ten caregivers attended to a one-month virtual synchronous course about EI. The emotional status of caregivers was registered one-month-previous and one-month-post program using comparative measures: The Trait Meta-Mood Scale (TMMS-24) and the Positive and Negative Affect Schedule (PANAS). Results: Median age of the ten caregivers was 48 years, 80% of women with a median care-time of 6 years. 50% of them were spouses of the patients. 60% of the patients were affected by stroke (hemorrhagic or ischemic cause). The main cognitive impairment of the patients reported by relatives was memory deficit. After re-ceiving training, favorable changes were found regarding emotional affect measured with the PANAS, both positive (increase) and negative (decrease), as well as with the TMMS-24-mood-repair area (p < 0.05). Conclusions: Training in EI helps caregivers to make their mood more positive and improve aspects of their emotional intelligence such as emotional regulation.

Background. Traumatic brain injury (TBI) is the main cause of disabilities over the industrialized countries. Cognitive decline appears in the chronic phase of the pathology consecutively to cellular and molecular processes. Here we described the use of KCC2, a neuronal-specific potassium-chloride transporters as potent biomarker to predict cognitive dysfunctions after TBI. Methods. Using neuronal and total exosomes collection from blood serum in control and TBI subjects we were able to anticipate the decline of cognitive performance. Results. After TBI, we observed a significative and persistant loss of KCC2 expression in the blood exosomes that is correlated to changes in network activity and cellular processes such as secondary neurogenesis. Also we correlated this KCC2 loss in expression to the appearance of the cognitive decline observed in mice and more particularly we correlate the KCC2 loss of expression to the appearance of the depressive-like behavior. Conclusion. According to our protocol, we were able to confirm our previous findings in agreement with the potential therapeutic effect of bumetanide in the prevention of the post traumatic depression after TBI, by restoring the KCC2 expression thus preventing the massive neuronal death of interneurons and the secondary neurogenesis effect observed in such model.

Scientific theories on the functioning and dysfunction of the human brain require a good understanding of both its development — before and after birth, and through maturation to adulthood — and its evolution from the ancestral primate brain. Adopting a complex-systems approach, here we propose that the apparent uniqueness of humans’ cognitive capacities might best be understood as emerging from multiple nested “virtuous cycles.” In particular, we propose that the intimate link that exists between oxygen metabolic loops, cortical expansion, and ultimately cognitive and social demands is a key driver of genetic developmental programs for the human brain. Overall, our proposed evolutionary model makes explicit mechanistic links between metabolism, molecular and cellular brain heterogeneity, and behaviour that may in time provide a clearer understanding of brain developmental trajectories and their disorders.

Fluorescence microscopy provides an unparalleled tool for imaging biological samples. However, producing high-quality volumetric images quickly and without excessive complexity remains a challenge. Here, we demonstrate a simple multi-camera structured illumination microscope (SIM) capable of simultaneously imaging multiple focal planes, allowing for the capture of 3D fluorescent images without any axial movement of the sample. This simple setup allows for the acquisition of many different 3D imaging modes, including 3D time lapses, high-axial-resolution 3D images, and large 3D mosaics.

Brain tumors are neoplasms with one of the highest mortality rates. Therefore, the availability of methods that allow the quick and effective diagnosis of brain tumors and selection of appropriate treatments is of critical importance for patient outcomes. In this study, coated blade spray-mass spectrometry (CBS-MS), which combines the features of microextraction and fast ionization methods, is applied for the analysis of brain tumors. In this approach, a sword-shaped probe is coated with a sorptive material to enable the extraction of analytes from biological samples. The analytes are then desorbed using only a few microliters of solvent, followed by the insertion of the CBS device into the interface on the mass spectrometer source. The results of this proof-of-concept experiment confirmed that CBS coupled to high-resolution mass spectrometry (HRMS) enables the rapid differentiation of two histologically different lesions: meningiomas and gliomas. Moreover, quantitative CBS-HRMS/MS analysis of carnitine, the endogenous compound, previously identified as discriminating metabolite showed good reproducibility with the variation below 10% when using a standard addition calibration strategy and deuterated internal standards for correction. The resultant data show that the proposed CBS-MS technique can be useful for on-site qualitative and quantitative assessments of brain tumor metabolite profiles.

In the current pilot study, we attempt to find out how double neurofeedback influences functional hemispheric asymmetry and activity. We examined 30 healthy participants (8 males; 22 females, mean age = 29; SD= 8). To measure functional hemispheric asymmetry and activity, we used computer laterometry in the ‘two-source’ lead-lag dichotic paradigm. Double biofeedback included 8 minutes of EEG oscillation recording with five minutes of basic mode. During the basic mode, the current amplitude of the EEG oscillator gets transformed into feedback sounds while the current amplitude of alpha EEG oscillator is used to modulate the intensity of light signals. Double neurofeedback did not directly influence the asymmetry itself but accelerated individual sound perception characteristics during dichotic listening in the preceding effect paradigm. Further research is needed to investigate the effect of double neurofeedback training on functional brain activity and asymmetry taking into account participants’ age, gender, and motivation.

Parenting has been robustly associated with offspring psychosocial development, and these effects are likely reflected in brain development. However, the claim that parenting influences offspring brain development in humans, as measured by structural and functional Magnetic Resonance Imaging (MRI), is subject to numerous methodological limitations. To interpret the state of the parenting and brain development literature, we review these limitations. Four limitations are common. First, most literature has been cross-sectional. Where longitudinal, studies rarely included multiple assessments of brain structure or function, precluding measurement of actual brain development. Second, parenting has largely been measured via selfor parent-report, as opposed to observational assessment. Third, there has been a focus on extreme forms of developmental adversity which do not necessarily lie on a continuum with normative parenting. Fourth, although not a limitation per se, studies have generally focused on negative as opposed to positive parenting behaviours. While not all studies are subject to all these limitations, the study of parenting in relation to offspring brain development is in its infancy.

Geometry deals both with analogical thinking and physical/biological observables. Naïve, common-sense descriptions of objects’ shapes and systems’ trajectories in geometric phase spaces may help experimental investigation. For example, very different biological dynamics, as the developmental growth patterns of the oldest known animal (the extinct Dickinsonia) and the human brain electric oscillations, display a striking analogy: when encompassed in abstract geometric spaces, their paths describe the same changes in curvature: from convex, to flat, to concave and vice versa. This dynamical behavior, anticipated by Nicholas de Cusa in his analogical account of “coincidentia oppositorum” (1440), helps to describe widespread biological paths in the manageable terms of concave, flat and convex curves on donut-like structures. Every trajectory taking place on such toroidal manifolds can be located, through a topological technique called Hopf fibration, into a four-dimensional space. We discuss how the correlation between Hopf fibration and Navier-Stokes equations allows us to treat the above-mentioned biological and neuroscientific curved paths in terms of flows taking place into a viscous fluid medium that can be experimentally assessed and quantified.

The French-Swiss Professor in inductive philosophy Richard Avenarius (1843-1896), the father of empirio-criticism together with Ernst Mach, is one of the most underrated and misunderstood philosophers ever. It mostly depends upon his terminology, which displays an insurmountable difficulty. However, influenced by the most innovative proposals of his times of transition between the idealistic/rationalist legacies and the new Materialism/scientific interpretation of reality – i.e, by cultural evolutionism, linguistics, biomechanics, entropy/energy and, above all, by the newborn experimental psychology-, he produced a complete system of philosophy and innovative methods of investigation of the laws of knowledge. Hints (chunk, scrap, fragments) of his original ideas can be found not only in philosophers of mind after him - such as Gestalt, phenomenalism, behaviourism, functionalism and cybernetics, autopoiesis, dynamical systems theory, embedded/embodied mind, free-energy principle of the brain – but also in recent neuroscientific theories – nervous transduction, electric spikes, cracking of neural code, multisensory integration -. Our aim is to provide the first chronological English summary of his masterpiece, the “Kritik”, to give the possibility to the (almost) totally unaware English speakers to appreciate such a neglected and innovative thinker.

The main neurovascular unit of the Blood Brain Barrier (BBB) consists of a cellular component, which includes endothelial cells, astrocytes, pericytes, microglia, neurons and oligodendrocytes, as well as a non-cellular component resulting from the extracellular matrix. The endothelial cells are the major vital component of the BBB able to preserve the brain homeostasis; these cells are situated along the demarcation line between the bloodstream and the brain. Therefore, an alteration or the progressive disruption of the endothelial layer may clearly impair the brain homeostasis. The proper functioning of the brain endothelial cells is generally ensured by two elements: 1) the presence of junction proteins; 2) the preservation of a specific polarity involving an apical-luminal and a basolateral-abluminal membrane. In view of the above, this review intends to identify the molecular mechanisms underlying BBB function and their changes occurring in early stages of neurodegenerative processes in order to develop novel therapeutic strategies aimed to counteract neurodegenerative disorders.

Hedgehog (Hh) proteins are prototypical morphogens known to regulate epithelial/mesenchymal interactions during embryonic development. In addition to its pivotal role in embryogenesis, the Hh signaling pathway may be recapitulated in post-natal life in a number of physiological and pathological conditions, including ischemia. This review highlights the involvement of Hh signaling in ischemic tissue regeneration and angiogenesis, with particular attention to the heart, the brain, and the skeletal muscle. Updated information on the potential role of the Hh pathway as a therapeutic target in ischemic condition is also presented.

A growing area in neurosciences is focused on the modeling and analysis the complex system of connections in neural systems, i.e. the connectome. Here we focus on the representation of connectomes by using graph theory formalisms. The human brain connectomes are usually derived from neuroimages; the analyzed brains are co-registered in the image domain and brought to a common anatomical space. An atlas is then applied in order to define anatomically meaningful regions that will serve as the nodes of the network - this process is referred to as parcellation. Recently, it has been proposed to perform atlas-free random brain parcellation into nodes and align brains in the network space instead of the anatomical image space to define network nodes of individual brain networks. In the network domain, the question of comparison of the structure of networks arises. Such question is tackled by modeling the comparison of brain network as a network alignment (NA) problem. In this paper, we first defined the NA problem formally, then we applied three existing state of the art of multiple alignment algorithms (MNA) on diffusion MRI-derived brain networks and we compared the performances. The results confirm that MNA algorithms may be applied in cases of atlas-free parcellation for a fully network-driven comparison of connectomes.

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized mainly by the gradual decay in neuronal function as a consequence of diverse degenerating events primarily including mitochondria dysfunction and cascades of neuro-immune reactions. Besides the acquired harmful reactive oxygen species (ROS), neurotoxins, and amyloid-beta (Aβ) and TAU pathologies in neurons, accumulating evidence with time underlined the roles of cytokines and growth factors in the AD pathogenesis. It may help us in evaluating the propensities and specific mechanism(s) of cytokines and factors impacting neuron upon apoptotic decline. Proinflammatory cytokines often induce inflammation in AD and AD-like pathogenesis in response to the apoptotic scenarios where some growth factors are involved in cytokinetic reactions to activate microglia and causing inflammation in AD. In this report, we comprehensively reviewed role of cytokines and chemokines in immune response to AD and neuropsychiatry. We provided insights into the neuroinflammation and the role of diverse factors including the pro-/anti-inflammatory cytokines, APP, TAU phosphorylation, glycation end products, complement system, and the role of glial cells. Also, we discussed the pathogenic and protective role of macrophage migration inhibitory factors, choroid plexus-, neurotrophic- and hematopoietic -related growth factors in AD. We further shed light on the availability and accessibility of the cytokines across the blood-brain barrier in AD pathophysiology. Taken together, the emerging role of these factors in AD pathology emphasized the importance of building novel strategies for an effective therapeutic/neuropsychiatric management of AD in clinics.

Post-concussion syndrome, recently recognized as a complication of mild traumatic brain injury, is considered a consequence of the summative effect of multiple concussions received over lifetime. In elderlies, the main mild brain trauma mechanism is fall (low impact force). Many falls are often not reported or noticed but may generate serious medical and medico-legal consequences. Our research question was to find if a single, very mild brain trauma can induce neuro-behavioral consequences in elderlies. One database was queried (PubMed – MeSH terminology) looking for histopathological, neuro-cognitive and behavioral changes that can be generated by sub-concussional trauma in senescent rodents, in comparison with young animals. 41 published research articles were selected. 17 of them used very mild brain trauma in young and senescent animals, in the same experiment (6 rats and 11 mice). 24 articles evaluated the effect of sub-threshold brain trauma in adult animals (no control group). Five trauma models were used (blast models were excluded). Neuro-inflammatory changes were detected immediate after very mild primary impact. In young animals, observed pathology disappeared fast (after 3 to 7 days). Increased apoptosis, mild axonal injury in white matter tracts plus maladaptive astrogliosis and microglial activation was stronger in aged animals, persisted over time (8 months) and significantly altered animals’ cognition and behavior. Associated preexisting pathology (hypertension, tau protein deposits, microbleeds, reactive inflammation) was often responsible for amplification of the primary impact results. As translation of observation is the weak spot of pathology and behavior animal research, further investigation is needed before to conclude that even a single, very mild brain trauma may have medical consequences on human senescent brain.

Background: New controversies have raised on brain death (BD) diagnosis when lesions are localized in the posterior fossa. Objective: To discuss the particularities of diagnosis BD in patients with posterior fossa lesions. Material and Methods. The author made a systematic review of literature on this topic. Results and Conclusions: A supratentorial brain lesion usually produces a rostrocaudal transtentorial brain herniation, resulting in forebrain and brainstem loss of function. In secondary brain lesions [i.e., cerebral hypoxia], the brainstem is also affected like the forebrain. Nevertheless, some cases complaining posterior fossa lesions [i.e., basilar artery thrombotic infarcts, or hemorrhages of the brainstem and/or cerebellum] may retain intracranial blood flow and EEG activity. In this article I discuss that if a posterior fossa lesion does not produce an enormous increment of intracranial pressure, a complete intracranial circulatory arrest does not occur, explaining the preservation of EEG activity, evoked potentials, and autonomic function. I also address Jahi McMath, who was declared braindead, but ancillary tests, performed 9 months after initial brain insult, showed conservation of intracranial structures, EEG activity, and autonomic reactivity to “Mother Talks” stimulus, rejecting the diagnosis of BD. Jahi McMath’s MRI study demonstrated a huge lesion in the pons. Some authors have argued that in patients with primary brainstem lesions it might be possible to find a in some cases partial recover of consciousness, even fulfilling clinical BD criteria. This was the case in Jahi McMath.

Tardive dyskinesia (TD) is a phenomenon predominantly observed as a result of the long-term use of dopamine receptor blockers (antipsychotics). TD is a group of involuntary, irregular hyperkinetic movements, mainly in the muscles of the face, eyelid muscles, lips, tongue, and cheeks, and less frequently in the limbs, neck, pelvis, and trunk. In some patients, TD takes on an extremely severe form, massively disrupting functioning, moreover, causing stigmatization and suffering. Deep brain stimulation (DBS), a method used, among others, in Parkinson's disease, is also an effective treatment for TD and often becomes a method of last resort, especially in severe, drug-resistant forms. The procedure is relatively new in TD, so the available reliable clinical studies are few and consist mainly of case reports. Unilateral and bilateral stimulation of two sites has proven efficacy in TD treatment. Most authors describe stimulation of the globus pallidus internus (GPi); less frequent descriptions involve the hypothalamic nucleus (STN). In the present paper, we provide up-to-date information on the stimulation of both mentioned brain areas. We also compare the efficacy of the two methods by comparing the two available studies, which included the largest groups of patients. Although GPi stimulation is more frequently used clinically, our initial analysis indicates comparable results (reduction of involuntary movements) with STN DBS.

This concept paper gives a narrative about intelligence from insects to the human brain, showing where evolution may have been influenced by the structures in these simpler organisms. The ideas also come from the author's own cognitive model, where a number of algorithms have been developed over time and the precursor structures should be codable to some level. Through developing and trying to implement the design, ideas like separating the data from the function have become architecturally appropriate and there have been several opportunities to make the system more orthogonal. Similarly for the human brain, neural structures may work in-sync with the neural functions, or may be slightly separate from them. Each section discusses one of the neural assemblies with a potential functional result, that cover ideas such as timing or scheduling, structural intelligence and neural binding. Another aspect of self-representation or expression is interesting and may help the brain to realise higher-level functionality based on these lower-level processes.

If the development of machine learning and artificial intelligence plays a role in many fields of research and technology today, it has a special relationship with neurosciences. Indeed, historically inspired by our knowledge of the brain, deep learning shares some vocabularies with neurosciences and can sometimes be considered a brain’s model. Taking the particular example of epileptic seizure, which can develop in any biological neural tissue, we raise the question if and how the models used for deep learning can capture or model these pathological events. This particular example is a starting point to discuss the nature, limits, and functions of these models, and what we expect from a model of the brain. Finally, we argue that a pluralistic approach leading to the integrated coexistence of different models is necessary to study the brain in all its complexity.

The blood brain barrier (BBB) is an essential component in regulating and maintaining the homeostatic microenvironment of the central nervous system (CNS). During the occurrence and development of glioblastoma (GBM), BBB is pathologically disrupted with markedly increased permeability. Due to the obstruction imposed by the BBB, strategies currently employed for GBM therapeutics still obtain a very low success rate and lead to systemic toxicity. Moreover, chemotherapy could promote pathological BBB functional restoration, accompanied with a prominent decrease of intracerebral therapeutics transportion during GBM multiple administration, resulting in chemotherapy failure for GBM treatment. The effective delivery of therapeutics into the brain still faces with severe challenges. Regulation of pathological BBB for enhanced transporting of therapeutics across the barrier may provide new opportunities for effective and safe treatment of GBM. This article reviews the structure and function of BBB in physiological state, the mechanisms underlying BBB pathological fenestration during the development of GBM, and the therapeutic strategies of GBM based on BBB intervention and therapeutic drugs transporting across the BBB.

Abstract—Low-frequency Fahræus–Lindqvist-driven (not blood pressure-driven) oscillations in the small vessels are crucial because oscillations in small vessels support nutrient supply. Understanding of this is critical in type 2 diabetes mellitus (T2DM) to develop therapeutic measures to prevent Alzheimer's Disease Related Dementias: vascular factors contribute to cerebrovascular disease as well as mild cognitive impairment and dementia, which are predicted to affect 152 million people by 2050 (Alzheimer's Disease International London, UK, 2019). In this clinical study, we performed functional near-infrared spectroscopy (fNIRS) of the forehead to investigate the effect of the Mini-Cog with three-item recall test on the prefrontal cortex (PFC) activation and the relative oscillatory power in the 0.01–0.02-Hz (Fahræus–Lindqvist effect) and 0.021–0.052 Hz (smooth muscle autonomic innervation) frequency bands in elderly (60 years and older) T2DM and age-matched controls. We found a significant (p<0.01) difference in the PFC activation between elderly subjects with T2DM and age-matched elderly controls. Moreover, power spectral density (PSD) analysis revealed a significantly lower relative power in 0.021–0.052 Hz (smooth muscle autonomic innervation) frequency band in elderly subjects with T2DM during the Mini-Cog three-item recall test. Furthermore, a drop in the oscillatory power in the 0.01–0.02-Hz frequency band during Mini-Cog three-item recall test was found more pronounced in the elderly subjects with T2DM. Therefore, our study highlighted portable brain imaging to capture cerebrovascular reactivity to cognitive load that may provide a biomarker of cerebrovascular dysfunction in T2DM.Clinical Relevance— Our study establishes forehead portable brain imaging for monitoring cerebrovascular function in T2DM under cognitive load.

Epigenetic mechanisms, including post-translational modifications of DNA and histones that influence chromatin structure, regulate gene expression during normal development, and are also involved in carcinogenesis and cancer progression. The histone methyltransferase G9a (euchromatic histone lysine methyltransferase 2, EHMT2), which mostly mediates mono- and dimethylation by histone H3 lysine 9 (H3K9), influences gene expression involved in embryonic development and tissue differentiation. Overexpression of G9a has been observed in several cancer types, and different classes of G9a inhibitors have been developed as potential anticancer agents. Here, we review the emerging evidence suggesting the involvement of changes in G9a activity in brain tumors, namely glioblastoma (GBM), the main type of primary malignant brain cancer in adults, and medulloblastoma (MB), the most common type of malignant brain cancer in children. We also discuss the role of G9a in neuroblastoma (NB) and the drug development of G9a inhibitors.

(1) Background: Extremely low alanine aminotransferase (ALT) levels are be-ing recognized as a risk factor of increasing mortality in the elderly in relation to frailty. In the elderly, both frailty and ischemic stroke are not only common, but also associated with mortality. This study aimed to investigate whether extremely low ALT levels increase the all-cause mortality rate in the elderly after ischemic stroke. (2) Methods: A retrospective review was performed on 901 patients with ischemic stroke admitted to a university-affiliated hospital between February 2014 and April 2019. The multivariate Cox proportional hazard analysis was performed to determine whether extremely low ALT lev-els are an independent risk factor of mortality in elderly patients after ischem-ic stroke. (3) Results: This study enrolled 323 older adults (age ≥65 years) who were first diagnosed with ischemic stroke. The mean age of the participants was 76.5 ± 6.6 years, mean survival time was 37.1 ± 20.4 months, and the num-ber of deaths was 96 (29.7%). The multivariate Cox proportional hazard analy-sis revealed that the risk factors for all-cause mortality in the elderly after is-chemic stroke were age, initial National Institutes of Health Stroke Scale score, serum creatinine, and extremely low ALT level (<10 U/L) at the time of diag-nosis (adjusted hazard ratio: 3.243, 95% confidence interval: 1.945–5.408; P < 0.001) (4) Conclusions: Extremely low ALT level at the time of diagnosis (<10 U/L) is an independent risk factor that increases the mortality rate in the el-derly after ischemic stroke.

We aim to determine the sleep correlates of age-related brain loss in a sample of middle-aged to older males with obstructive sleep apnea. We evaluated consecutive treatment naïve male patients with OSA (AHI≥15 events/hr) without dementia, stroke or heart disease, from January to November of 2019. We collected demographic variables, vascular risk factors, and sleep questionnaires. We also obtained computerized neurocognitive testing with the Go-No-Go Response Inhibition Test, Stroop Interference Test, Catch Game Test, Staged Information Processing Speed Test, Verbal Memory Test and Non-Verbal Memory Test. We derived age and education adjusted domain-specific Z-scores for global cognition, memory, attention, processing speed and executive function. We used brain MRI T1-weighted images to derive total hippocampal and gray matter volumes. Partial correlations evaluated associations between the ISI, AHI, and oxygen level during sleep, with cognitive domains and brain volumes. Sixteen participants, age 40-76 years, 73% Hispanic/Latino, with mean AHI=48.9±25.5 and mean oxygen saturation of 91.4±6.9% during sleep. Hypertension was seen in 66% and diabetes in 27%. We observed that ISI and oxygen level during sleep had strong correlations with brain volumes and cognition. These preliminary findings may aid in developing future strategies to improve age-related brain loss in OSA.

A growing body of evidence indicates that aging of the brain is strictly related to the decline of energy metabolism. In particular, in older adults, the neuronal metabolism of glucose declines steadily resulting in a growing deficit of ATP production. The decline is evoked by deficient NAD recovery in the salvage pathway and subsequent impairment of the Krebs cycle. NAD deficit impairs also the activity of NAD-dependent enzymes. All these open vicious circles of neurodegeneration and neuronal death. Some brain structures are particularly prone to aging and neurodegeneration. These are pathological foci of neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease. This review article summarizes the impacts and mutual relationships between metabolic processes both on neuronal and brain levels. It also provides directions on how to reduce the risk of neurodegeneration and protect the elderly against neurodegenerative diseases.

Glioma tumors are one of the most devastating cancer types. Of the different glioma tumors, glioblastoma is the most advanced stage with the worst prognosis. Current therapies are still unable to provide an effective cure. Recent advantages in oncolytic immunotherapy have generated great expectations in the cancer therapy field. The use of oncolytic viruses (OV) in cancer treatment is one of those immune-therapeutic alternatives. OV have a double oncolytic action by both, directly destroying the cancer cells, sparing the patient’s life, and stimulating a tumor specific immune response to revert the ability of tumors to escape the control of the immune system. OV are one promising alternative to conventional therapies in glioma tumor treatment. Several clinical trials have proven the feasibility to use some viruses to specifically infect tumors eluding undesired toxic effects in the patient. Here we have revisited the literature in order to describe the main OV proposed so far as therapeutic alternatives to destroy glioma cells in vitro and trigger tumor destruction in vivo. Some clinical trials are exploring the use of this therapy as an alternative were other approaches provide limited hope.

Lewis et al. published an important and timely necessary article about the determination of death by neurological criteria, revising the Uniform Determination of Death.The acceptance of brain death (BD) has been progressively accepted beginning at the late 1950s. Nonetheless, contentious brain-death cases have recently raised new controversies about the diagnosis of BD, such as the Jahi McMath case, extensively covered by the US and international press. Jahi McMath meant a terrible tragedy for her and her family. But further than this gloomy story, the case has also raised confusion and challenging qualms about a fundamental query: how we confirm whether a person is dead or alive? Since 1981, the Uniform Determination of Death Act (UDDA) has served as the legal foundation for the medical practice of determining death. But, although death by neurologic criteria is considered legal death throughout the United States, several recent lawsuits have quizzed the rightfulness the authority of the UDDA to declare death by neurological criteria. This issue explains the importance of Lewis’s et al. paper. In this article I want to present the historical procedure for issuing a law in Cuba for the determination and certification of death. Of course, it is impossible to compare our country with USA. Cuba is a small and developing country, in which a law encompasses a national scenery, in contrast with USA, a multistate nation.

Visual imagery, i.e., the mental experience of an object occurring in the absence of external visual stimulus, might encompass diverse content according to different observers. Further, subjectively experienced time is encoded in the later entorhinal cortex. Starting from these two observations, and considering Einstein’s account of spacetime, we show how, in terms of special relativity, the content of visual imagery is not stationary and fixed, rather depends on the standpoint of the observer. We elucidate how the subjective definition of time (perceived by our mind as static) might give rise to modifications in the length of the imagined object which are experimentally assessable and quantifiable. In particular, based on recent neuroscientific literature, we show how changes in our mental time windows are able to squeeze the visual content of mental imagery.

The central nervous system (CNS) and the human gastrointestinal (GI) tract communicate through the gut-brain axis (GBA). Such communication is bi-directional and involves neuronal, endocrine and immunological mechanisms. The scientific data are mounting that gut microbiota is a source of a number of neuroactive and immunocompetent substances, which shape the structure and function of brain regions involved in control of emotions, physical activity and cognition. Most of GI maladies are associated with altered transmission within the GBA and influenced both by genetic and environmental factors. Current treatment protocols widely advocated for the treatment of GI disorders may positively or adversely affect the composition of intestinal microbiota with diverse impact on therapeutic outcome. The alterations of gut microbiota have been associated with mood and depressive disorders. and mental health is frequently altered in the course of many GI and non-GI ailments. Deregulation of the GBA may constitute a grip point for the development of diagnostic tools and personalized microbiota-based therapy. For example next generation sequencing (NGS) offers detailed analysis of microbiome footprints in patients with mental and GI disorders. Psychobiotics are new class of beneficial bacteria, with documented efficacy in the treatment of gut-brain axis disorders.

1) Introduction: Brain parcellation is an important processing step in the analysis of structural brain MRI. Existing software implementations are optimized for fully developed adult brains, and provide inadequate results when applied to neonatal brain imaging. 2) Methods: We developed a semi-automated pipeline, NeBSS, for extracting 50 discrete brain structures from neonatal brain MRI, using an atlas registration method that leverages the existing ALBERT neonatal atlas 3) Results: We demonstrate a simple linear workflow for neonatal brain parcellation. NeBSS is robust to variation in imaging acquisition protocol and magnet field strength. 4) Conclusion: NeBSS is a robust pipeline capable of parcellating neonatal brain MRIs using a simple processing workflow. NeBSS fills a need in clinical translational research in neonatal imaging, where existing automated or semi-automated implementations are too rigid to be successfully applied to multi-center neuroprotection studies and clinically heterogeneous cohorts. The software is open source and freely available.

A Traumatic brain injury (TBI) is among the main causes of sudden death after head trauma. These injuries can result in severe degeneration and neuronal cell death in the CNS, including the retina which is a crucial part of the brain responsible for perceiving and transmitting visual information. The long-term effects of mild-repetitive TBI (rmTBI) are far less studied thus far, even though damages induced by repetitive injuries occurring in the brain are more common, especially amongst athletes. rmTBI can also have a detrimental effect on the retina and the pathophysiology of these injuries are likely to differ from the severe TBI (sTBI) retinal injury.Here we showed how rmTBI and sTBI can dissimilarly affect the retina. Our results indicate an increase in the number of activated microglial cells and Caspase3-positive cells in the retina in both traumatic models, suggesting a rise in the level of inflammation and cell death after TBI. The pattern of microglial activation appears evenly distributed and widespread but differs amongst the various retinal layers. sTBI induced microgial activation in both the superficial and deep retinal layers. In contrast to sTBI, no significant change occurred following the repetitive mild injury in the superficial layer, only the deep layer (spanning from the inner nuclear layer to the outer plexiform layer) shows microglial activation. This difference suggests that alternate response mechanisms play a role in the case of the different TBI incidents. The Caspase3 activation pattern showed a uniform increase in both the superficial and deep layers of the retina. This suggests a different action in the course of the disease in sTBI and rmTBI models and points to the need for new diagnostic procedures.Our present results suggest that the retina might serve as such a model of head injuries since the retinal tissue reacts to both forms of TBI and is the most accessible part of the human brain.

Growing evidence suggests a possible involvement of the intestinal microbiota in generating new neurons, but a detailed breakdown of the microbiota composition is lacking. In this report, we systematically reviewed preclinical rodent reports addressing the connection between the composition of the intestinal microbiota and neurogenesis and neurogenesis-affecting neurotrophins in the hippocampus. Various changes in bacterial composition from low taxonomic resolution at the phylum level to high taxonomic resolution at the species level were identified. As for neurogenesis, studies predominantly used doublecortin (DCX) as a marker of newly formed neurons or bromodeoxyuridine (BrdU) as a marker of proliferation. Brain-derived neurotrophic factor (BDNF) was the only neurotrophin found researched in relation to the intestinal microbiota. Phylum Actinobacteria, genus Bifidobacterium and genus Lactobacillus found the strongest positive while phylum Firmicutes, phylum Bacteroidetes and family Enterobacteriaceae as well as germ-free status, showed the strongest negative correlation towards neurogenesis or BDNF mRNA expression. Age, short-chain fatty acids (SCFA), obesity and chronic stress were recurring topics in all studies identified. Overall, these findings add to the existing evidence of a connection between microbiota and processes in the brain. To better understand this interaction, further investigation based on analyses of higher taxonomic resolution and clinical studies would be a gain to the matter.

Obesity in pregnancy induces metabolic syndrome, low-grade inflammation, altered endocrine factors, placental function, and the maternal gut microbiome. All these factors impact fetal growth and development, including brain development. The lipid metabolic transporters of the maternal-fetal-placental unit are dysregulated in obesity. Consequently, the transport of essential long-chain PUFAs for fetal brain development is disturbed. The mother’s gut microbiota is vital in maintaining postnatal energy homeostasis and maternal-fetal immune competence. Obesity during pregnancy changes the gut microbiota, affecting fetal brain development. Obesity and a high-fat diet in pregnancy can induce placental and intrauterine inflammation and thus influence the neurodevelopmental outcomes of the offspring. Several epidemiological studies observed an association between maternal obesity and adverse neurodevelopment. This review discusses the effects of maternal obesity and gut microbiota on fetal neurodevelopment outcomes. In addition, the possible mechanisms of the impacts of obesity and gut microbiota on fetal brain development are discussed.

Segmentation is an important step in medical imaging. In particular, machine learning, especially deep learning, has been widely used to efficiently improve and speed up the segmentation process in clinical practice. Despite the acceptable segmentation results of multi-stage models, little attention was paid to the use of deep learning algorithms for brain image segmentation, which could be due to the lack of training data. Therefore, in this paper, we propose a Generative Adversarial Network (GAN) model that performs transfer learning to segment MRI brain images.Our model enables the generation of more labeled brain images from existing labeled and unlabeled images. Our segmentation targets brain tissue images, including white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). We evaluate the performance of our GAN model using a commonly used evaluation metric, which is Dice Coefficient (DC). Our experimental results reveal that our proposed model significantly improves segmentation results compared to the standard GAN model. We observe that our model is 2.1–10.83 minutes faster than stat-of-the-art-models.

Pathologies of the blood brain barrier (BBB) have been linked to a multitude of CNS disorders whose pathology is poorly understood. Cortical spreading depression (CSD) has long been postulated to be involved in the underlying mechanisms of these disease states, yet full understanding remains elusive. This study utilized an in vitro model of the BBB with b.End3 murine endothelial cells to investigate the role of CSD in BBB pathology by characterizing effects of the release of major pronociceptive substances on BBB functional integrity using TEER screening, transcellular uptake, and immunoreactive methods in concert with global proteome and phospho-proteomic approaches. Findings demonstrated relocalization and functional alteration to proteins associated with the cytoskeleton and endothelial tight junctions. Pathologic mechanisms induced by individual substances released during CSD were found to have unique phosphorylation signatures in phospho-proteome analysis, identifying Zona Occludens 1 as a possible pathologic “checkpoint” of the BBB. Utilizing these phosphorylation signatures, possible novel diagnostic methods may be developed for neurological diseases and warrants further investigation.

The study of the brain networks using analysis of electroencephalography (EEG) data based on statistical dependencies (functional connectivity) and mathematical graph theory concepts is common in neuroscience and cognitive sciences for examinations of patient and healthy individuals. The Consciousness Fields according to Taheri theory and applications in the optimization of system under study have been investigated in various studies. In this study, we examine the results of working with Faradarmani Consciousness Field (FCF) in the brain of Faradarmangars. Faradarmangars are one of the necessary components in mind mediation of the function of Faradarmani Consciousness Fields according to Taheri. For this purpose, the functional and effective connectivity and the corresponding brain graphs of EEG from the brain of Faradarmangars is compared with that of non Faradarmangar groups during FCF connection. According to the results of the present study, the brain of the Faradarmangars shows significant decreased activity in delta (BA8), beta2 (BA4/6/8/9/10/11/32/44/47) and beta3 (in 34 of 52 BA) frequency bands mainly in frontal lobe and after that in parietal and temporal lobes in the comparison with the non Faradarmangars. Moreover, the functional and effective connectivity analysis in the frontal network shows dominant multiple decreased connectivity mainly in the case of beta3 frequency band in all parts of the frontal network. On the other hand, the graph theory analysis of the Faradarmangar brain shows an increase in the activity of the O2-T5-F4-F3-FP2-F8 areas and significant decrease in the characteristic path length and increases in global efficiency, clustering coefficient and transitivity. In conclusion, the unique higher graph function efficiency and the reduction in the brain activity and connectivity during the Faradarmani Consciousness Field mind mediation, shown the passive and detector like function of the human brain in this task.

Conclusions: Meningiomas with histopathological CNS invasion show a higher proliferative activity.

It is proposed to incorporate the concepts of brain microbiota and microbial consciousness in the Orchestrated Objective Reduction (Orch OR) theory of human consciousness with the goal of increasing its explanatory and predictive powers. If consciousness arises from quantum computations in cytoskeletal structures inside human neurons, there is no theoretical impediment at hypothesizing that it might also occur in the cytoskeletal structures of the microbes resident in the human brains. If the concept of the brain microbiota is integrated in a general Orch OR theory, its explanatory and predictive powers would be vastly increased.

The medial septum (MS), as part of the basal forebrain, supports many physiological functions, from sensorimotor integration to cognition. With often reciprocal connections with a broad set of peers at all major divisions of the brain, the MS orchestrates oscillatory neuronal activities throughout the brain. These oscillations are critical in generating sensory and emotional salience, locomotion, maintaining mood, supporting innate anxiety, and governing learning and memory. Accumulating evidence points out that the physiological oscillations under septal influence are frequently disrupted or altered in pathological conditions. Therefore, the MS may be a potential target for treating neurological and psychiatric disorders with abnormal oscillations (oscillopathies) to restore healthy patterns or erase undesired ones. Recent studies have revealed that the patterned stimulation of the MS alleviates symptoms of epilepsy. We discuss here that stimulus timing is a critical determinant of treatment efficacy on multiple time scales. On-demand stimulation may dramatically reduce side effects by not interfering with normal physiological functions. A precise pattern-matched stimulation through adaptive timing governed by the ongoing oscillations is essential to effectively terminate pathological oscillations. The time-targeted strategy for the MS stimulation may provide an effective way of treating multiple disorders including Alzheimer’s disease, anxiety/fear, schizophrenia, and depression, as well as pain.

Diet plays a pivotal role in the overall health of an individual. Not only does it help carry out and regulate certain physiological functions, but it also can determine the composition of the gut microbiome. While the relative number of microorganisms that make up the gut microbiome vary between individuals and can be dependent on different environmental factors, there is evidence to suggest that composition of the microbiome can correlate with overall health or disease. When the GI microbiome is disturbed or suddenly changes it results in microbiome dysbiosis, a condition that correlates with the presence of certain diseases. Diseases linked to microbiome dysbiosis range from metabolic disorders, inflammatory bowel diseases to disorders of the brain. Many of these diseases are linked to the connection between the brain and the gut, known as the brain-gut axis. This bidirectional communication is important to maintain normal intestinal function, but is also responsible for the GI response to emotions as well as the emotional response to GI disturbances. By exploiting the interaction between microbiome health and nutrition, diet can be used to alleviate disease symptoms, protect against the development of certain conditions, and better maintain overall health. This review will examine the effects of nutrition on the microbiome, diseases linked to disruption of the normal microbiome, and the way that altering the diet can mitigate symptoms or prevent disease.

Brain development during the prenatal period is rapid and unparalleled by any other time during development. Biological systems undergoing rapid development are at higher risk for disorganizing influences. Therefore, certain prenatal exposures impact brain development, increasing risk for negative neurodevelopmental outcome. While prenatal exposures have been associated with cognitive and behavioral outcomes later in life, the underlying macroscopic brain pathways remain unclear. Here, we review studies investigating the association between prenatal exposures and infant brain development focusing on prenatal exposures via maternal physical health factors, maternal mental health factors, and maternal drug and medication use. Further, we discuss the need for studies to consider multiple prenatal exposures in parallel and suggest future directions for this body of research.

This study examined the effects of group art therapy on depression, burden, and self-efficacy in primary family caregivers of patients with brain injuries. This was a quasi-experimental, nonequivalent control group and a pre- and post-test design. This study was carried out in one national rehabilitation hospital targeting 41 primary family caregivers of patients with brain injuries. Group art therapy intervention was carried out three days per week for 12 times over four consecutive weeks. The experimental group (n = 20) received group art therapy, whereas the control group (n = 21) did not. We used a time difference method to minimize the risk of contaminating the control group by sampling sequentially. The experimental group showed a significantly greater decrease in burden (t = 2.462, p = 0.020) and significantly greater improvement in self-efficacy (t = −6.270, p &lt; 0.001) than the control group. Group art therapy may be an effective nursing intervention for primary family caregivers of patients with brain injuries.

This review systematically explored structural, functional, and metabolic features of the cisgender brain compared with the transgender brain before hormonal treatment and the heterosexual brain compared to the homosexual brain from the analysis of the neuroimaging literature up to 2018, and identified and discussed subsequent studies published up to March 2021. Our main aim was to help identifying neuroradiological brain features that have been related to human sexuality to contribute to the understanding of the biological elements involved in gender identity and sexual orientation. We analyze 39 studies on gender identity and 24 on sexual orientation. Our results suggest that some neuroanatomical, neurophysiological, and neurometabolic features in transgender individuals resemble those of their experienced gender despite the majority resembling those from their natal sex. In homosexual individuals the majority resemble those of their same sex heterosexual population rather than their opposite sex heterosexual population. However, it is always difficult to interpret findings with non-invasive neuroimaging. Given the gross nature of these measures, it is possible that more differences too subtle to measure with available tools yet contributing to gender identity and sexual orientation could be found. Conflicting results contributed to the difficulty of identifying specific brain features which consistently differ between cisgender and transgender or between heterosexual and homosexual groups. The small number of studies, the small-to-moderate sample size of each study, and the heterogeneity of the investigations made it impossible to meta-analyze all the data extracted. Further studies are necessary to increase the understanding of the neurological substrates of human sexuality.

The performance of choice-reaction tasks during athletic movement has been demonstrated to evoke unfavorable lower limb biomechanics. However, the mechanism of this observation is unknown. We conducted a systematic review examining the association between 1) the biomechanical and functional safety of unplanned sports-related movements (e.g. jumps/runs with spontaneously indicated landing leg/cutting direction) and 2) markers of perceptual-cognitive function (PGF). A literature search in three databases (Pubmed, ScienceDirect, Google Scholar) identified five relevant articles. Study quality, rated by means of a modified Downs & Black checklist, was moderate to high (average: 13.5/16 points). Four of five papers, in at least one parameter, found either an association of lower PGF and reduced task safety or significantly reduced task safety in low vs. high PGF performers. Yet, as a) the outcomes, populations and statistical methods of the included trials were highly heterogeneous and b) only two out of five studies had an adequate control condition (pre-planned movement task), evidence was classified as conflicting. In sum, PGF may represent a factor increasing injury risk during unplanned sports-related movements but future research strengthening the evidence of this association is warranted.

Background: Coronavirus disease (COVID-19) related pneumonia is leaded by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), which infects host cells through receptors named Angiotensin-converting enzyme 2 (ACE2). Smoking is thought to be related to poor disease prognosis, as a large amount of evidence highlights the negative effects of smoking on lung health and its causal relationship with various respiratory diseases. Methods: We first evaluated the role of ACE2 expression level with tobacco effect. And correlation analyses were used to identify the related genes of ACE2 both in smoker trait and human normal multi-tissues. After intersections, hub genes were later used to further GSEA and co-regulated mechanisms were explored by GeneMANIA. We used UALCAN to perform survival curves of pan-cancers included 33 types of cancers. New clinical model of top co-occurrence cancer type was constructed and validated. Results: Effected by cigarette smoking, the expression level of ACE2 expressed statistically upwards in current smokers compared with never smokers, upwards in groups after acute smoke exposed compared with normal control. But no strong evidence detected in third-hand smoke, as poor amounts of samples, only 4. A little trend of expressing upwards became in groups after third-hand smoke compared with groups after clean air exposing. 4 genes included PIR, ADH7, AKR1C2 and AKR1C3 were identified as ACE2 related genes in smoker trait and human normal multi-tissues. Then, we made the survival curves of pan-cancers in 4 genes. Brain lower grade glioma was the co-occurrence type as both ACE2, PIR and AKR1C3 had the significantly prognostic situation. Later, we made the new clinical prediction model as the C-index was 0.827 and the Area Under Curves (AUCs) of 1-year survival, 2-year survival and 3-year survival were 0.921(95%CI, 0.882-0.961), 0.911(95%CI, 0.860-0.962) and 0.878(95%CI, 0.818-0.939). In inner validation, the AUCs of 1-year survival, 2-year survival and 3-year survival were 0.777(95%CI, 0.640-0.914), 0.916(95%CI, 0.842-0.990) and 0.888(95%CI, 0.768-1.000). In outer validation one, the AUCs of 1-year survival, 2-year survival and 3-year survival were 0.764(95%CI, 0.672-0.856), 0.848(95%CI, 0.783-0.913) and 0.748(95%CI, 0.656-0.841). And in outer validation two the AUCs of 1-year survival, 2-year survival and 3-year survival were 0.740(95%CI, 0.654-0.826), 0.766(95%CI, 0.688-0.843) and 0.794(95%CI, 0.721-0.866). Conclusions: In our study, we compared the ACE2 expression level between smokers and non-smokers crowds and identified associated hub genes. Then we explored the further role of hub genes in tumor fields to identify the correlation and influence between the avoidable host factors such as smoking on COVID-19 contamination and tumor. ACE2 and AKR1C3 are potential prognostic genes for brain lower grade glioma, and we created the web dynamic nomogram and encapsulation app through validations.

We extend our high-resolution MRI-based Finite Element (FE) head model, previously presented and validated in [1–3], by considering the heterogeneities of the white matter structures captured through the use of Magnetic Resonance Elastography (MRE). This approach imparts more sophistication to our numerical model and yields results that more closely match experimental results. It is found that the peak pressure more closely matches the experiments as compared to the heterogeneous case. Qualitatively, we find differences in stress wave propagation near the corpus callosum and the corona radiata, which are stiffer on average than the global white matter. We are able to study the effects of these stiff structures on transient stress wave propagation within the cerebrum, something that cannot be done with a homogenized material model.

This study evaluates various safety aspects of standardized impacts that cyclists may suffer while wearing a bicycle helmet, by combining a partially validated finite element model of the cranio-cervical region and a newly developed bicycle helmet model. Under EN 1078 standardized impact conditions, the results of simulated impact tests show that the helmet can absorb 40% to 50 % of the total impact energy at impact velocities above 4 m/s. Further, based on a relationship between Head Injury Criterion and the risk of injury from field data, the results of the simulations suggest that minor injuries may occur at impact velocities of 10 km/h, serious injuries at 15 km/h, and severe injuries at 20 km/h. Fatal injuries will likely occur at impact velocities of 30 km/h and higher.

Periodic travelling waves are observed in various brain activities including visual, motor, language, sleep, and so on. There are several neural field models describing periodic waves assuming nonlocal interaction and, possibly, inhibition, time delay, or some other properties. In this work we study the influence of asymmetric connectivity functions and of time delay on the emergence of periodic waves and on their properties. Nonlinear wave dynamics is studied, including modulated and aperiodic waves. Multiplicity of waves for the same values of parameters is observed. External stimulation in order to restore wave propagation in a damaged tissue is discussed.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has become an effective and widely used tool in the treatment of Parkinson’s disease (PD). STN-DBS has varied effects on speech. Clinical speech ratings suggest worsening following STN-DBS, but quantitative intelligibility, perceptual, and acoustic studies have produced mixed and inconsistent results. Improvements in phonation and declines in articulation have frequently been reported during different speech tasks under different stimulation conditions. Questions remain about preferred STN-DBS stimulation settings. Seven right-handed, native speakers of English with PD treated with bilateral STN-DBS were studied off medication at three stimulation conditions: stimulators off, 60 Hz (low frequency stimulation - LFS), and the typical clinical setting of 185 Hz (High frequency - HFS). Spontaneous speech was recorded in each condition and excerpts were prepared for transcription (intelligibility) and difficulty judgements. Separate excerpts were prepared for listeners to rate abnormalities in voice, articulation, fluency, and rate. Intelligibility for spontaneous speech was reduced at both HFS and LFS when compared to STN-DBS off. Speech produced at HFS was more intelligible than that produced at LFS, but HFS made the intelligibility task (transcription) subjectively more difficult. Both voice quality and articulation were judged to be more abnormal with STN-DBS on. STN-DBS reduced the intelligibility of spontaneous speech at both LFS and HFS but lowering the frequency did not improve intelligibility. Voice quality ratings with STN-DBS were correlated with the ratings made without stimulation. This was not true for articulation ratings. STN-DBS exacerbated an existing voice disorder and may have introduced new articulatory abnormalities.

The physics of the human brain has two components – basic physics common to all mammals and the physics of thinking inherent only in man. The development of the mental component of the structural and functional organization of the brain in phylogeny was associated with the chiral factor of the external environment, and in ontogenesis - with the social factor. The sensitivity of the brain to these factors was based on the single-connected nature of its aqueous basis, the mechanism of electromagnetic induction, and the features of the thermodynamics of the brain in a state of night sleep. In order to unify the description of the mechanism of electromagnetic processes in the brain, the concept of a quasiphoton has been introduced, combining all forms of excitation of electronic and molecular-cellular structures of the brain. Equivalent schemes of vibrational contours of neural network elements and macrostructures of the brain are proposed. Estimates of the kinetic parameters (activation energy, velocity) of the physical processes underlying the energy-information exchange of the brain with the external environment are made. Mechanisms of operative (physical) and permanent (chemical) memory of the brain, including a model of nonlocal quantum correlations, are discussed.

Brain cancer is the tenth leading cause of death in the U.S. Glioblastoma multiforme (GBM) is the most lethal primary malignant central nervous system tumor in adults. The present study employed samples from 1985-2014 to discover the difference in prognosis among glioblastoma subtypes after the evolution of treatment modalities over the past few years. The current study aims to find the differences between Glioblastoma multiforme (GBM) and giant cell glioblastoma (GCG) in terms of prognosis among adults and elderly patients in the U.S. This study is a historical cohort type of study and is conducted on adults and elderly individuals with GBM or GCG from the years 1985-2014 in the U.S. Data were collected from the Surveillance, Epidemiology, and End Results Program (SEER) database. The study exposure was GBM or GCG and the outcome was mortality. The potential confounders were age, sex, race, ethnicity, year of diagnosis, primary site, and surgery. A chi-square test was used for categorical data. A univariate analysis was used for variables having a p-value < 0.05. Potential confounders were selected and evaluated using multivariate logistic regression models to calculate the odds ratio with stepwise selection. The study sample was 25,117. The incidences of GBM and GCG were not similar in relation to age group. Also, Spanish-Hispanic ethnicity was independently protective of GBM and GCG as compared to Non-Spanish-Hispanic ethnicity patients with GBM have a higher mortality rate than do GCG patients. The mortality rate was higher among patients diagnosed before 2010. In conclusion, GCG was not statistically significant in association to reduced mortality. Non-Spanish-Hispanics with GBM or GCG had a higher mortality rate than did Spanish-Hispanics. Factors such as being female, being age >59, and having a year of diagnosis before 2010 were independently associated with increased mortality.

During the exploration of the surrounding environment, the brain links together external inputs, giving rise to perception of a persisting object. During imaginative processes, the same object can be recalled in mind even if it is out of sight. Here, topological theory of shape provides a mathematical foundation for the notion of persistence perception. In particular, we focus on ecological theories of perception, that account for our knowledge of world objects by borrowing a concept of invariance in topology. We show how a series of transformations can be gradually applied to a pattern, in particular to the shape of an object, without affecting its invariant properties, such as boundedness of parts of a visual scene. High-level representations of objects in our environment are mapped to simplified views (our interpretations) of the objects, in order to construct a symbolic representation of the environment. The representations can be projected continuously to an environmental object that we have seen and continue to see, thanks to the mapping from shapes in our memory to shapes in Euclidean space.

A brain-computer interface for controlling elements commonly used at home is presented in this paper. It includes the electroencephalography device needed to acquire signals associated to the brain activity, the algorithms for artefact reduction and event classification, and the communication protocol.

Stereotactic radiosurgery (SRS) is considered the initial treatment for lung cancer patients with small-sized and limited number of brain metastases. The objective of this study was to assess clinical outcomes of SRS treatment using CyberKnife (CK) for recursive partitioning analysis (RPA) class II/III patients with one to three brain metastases from lung cancer and identify which patients in the high RPA class could benefit from SRS. A total of 48 lung cancer patients who received CK-based SRS for their metastatic brain lesions from 2010 to 2017 were retrospectively analyzed. Radiographic response was evaluated during follow-up period. Overall survival (OS) and intracranial progression-free survival (IPFS) were calculated and prognostic variables associated with OS and IPFS were evaluated. Median follow-up time was 6.6 months. Local control rates at 6 months and 1-year following SRS were 98% and 92%, respectively. The median OS of all patients was 8 months. One-year and 2-year OS rates were 40.8% and 20.9%, respectively. In multivariate analysis, uncontrolled primary disease (p = 0.008) and ECOG performance status of 2 or 3 (p = 0.001) were independent prognostic factors for inferior OS. These two factors were also significantly associated with inferior IPFS. In subgroup analysis according to RPA class, primary disease status was the only prognostic factor, showing statistically significant OS differences in both RPA class II and III (controlled vs. uncontrolled: 41.1 vs. 12.3 months in RPA class II, p = 0.031; 26.9 vs. 4.1 months in RPA class III, p = 0.011). Our results indicated that SRS could be an effective treatment option for RPA class II/III patients with brain metastases from lung cancer in the modern treatment era. SRS might be particularly considered for patients with controlled primary disease.

P-glycoprotein (Pgp) determines resistance to a broad spectrum of drugs in glioblastoma multiforme (GB) because it is highly expressed in GB stem cells and in brain-blood barrier (BBB), the peculiar endothelium surrounding brain. Inhibiting Pgp activity in BBB and GB is still an open challenge. Here, we tested the efficacy of a small library of tetrahydroisoquinoline derivatives with an EC₅₀ for Pgp < 50 nM, in primary human BBB cells and in patients-derived GB, from which we isolated differentiated/adherent cells (AC, i.e. Pgp-negative/doxorubicin-sensitive cells) and stem cells (neurospheres, NS, i.e. Pgp-positive/doxorubicin-resistant cells). At 1 nM, 3 compounds increased the delivery of doxorubicin, a typical substrate of Pgp, across BBB monolayer, without altering expression and activity of other transporters. The compounds increased the drug accumulation within NS, restoring necrosis, apoptosis and reduction in cell viability induced by doxorubicin. In co-culture systems, the compounds added to the luminal face of BBB increased the delivery of doxorubicin to NS growing under BBB and rescued the drug’s cytotoxicity. Our work identified new ligands of Pgp active at low nanomolar concentrations, that effectively reduce Pgp activity in BBB and GB, and can improve chemotherapy efficacy in this tumor.

Objective: It was aimed to investigate the cerebral vascular territories in stroke patients with NVAF as an etiologic factor. Material and Methods: A total of 104 patients who were referred to our hospital between January 2015 and September 2016, who were over 55 years of age, identified or documented as having a standard ECG or Holter ECG record on their medical history, and diagnosed with stroke were included. Our study was designed as a retrospective analysis of prospective data. Detailed history, physical examination and electrocardiography (ECG) evaluations of the patients were performed. Descriptive statistics were used in the detection of findings, and t-test, Pearson-square test and Fisher's exact test were used for differences analysis. Results: 53.8% (N = 56) of the patients were male and 46.2% (N = 48) were female. The mean age was 73.5. MCA was the most common site of vascular involvement in NVAF-dependent strokes. In MCA vascular territory, ischemic infarcts were detected most frequently in the upper and lower divisions. SCA and PCA followed MCA. Approximately 64% of the NVAF-related strokes were anterior circulation infarction (ASE) and 22% were posterior circulation infarct (PSE). There was a significant difference in age and past stroke history factors in favor of ASE (p<0.05). There was no significant difference between ASE and PSE in HT, cardiac history and DM factors (p>0.05). Conclusion: It was emphasized that the area of the vessel that underwent ischemia in the acutely displayed infarcts and the etiological factor for this vessel area could be predicted

Metabolomic analysis of biological fluids and tissues has become an increasingly routine tool in the biological toolbox. However, challenges remain to be overcome, including developing strategies to maximise coverage of the metabolome without requiring large sample volumes. Here we describe a multimodal strategy that combines data using both LC-MS and GC-MS from a unique vial with a sample of plasma (20µl) or a sample of brain tissue (3mg). Using a split phase extraction the non-aqueous phase was analyzed by reversed phase (RP) LC-MS, whilst the aqueous phase was analyzed using hydrophilic liquid interaction chromatography (HILIC)LC-MS, with both phases also analysed using GC-MS after derivatization of the extract. Analytical performance was assessed in 7 rat cerebellum samples and a pilot study of 40 plasma samples (20 vs. 20: AD vs. healthy controls). The method, which uses four hours of instrument time, measured 20,707 metabolite features in brain samples and 17,266 in plasma samples, from those 44.1% features displayed CV’s below 15% and 75.2% below 30%. The method has potential to resolve subtle biological differences and to correlate metabolite composition directly to clinical outcomes including MMSE, age and ADCS-ADL. This method can acquire in the order of 20K metabolic features when low volumes are available.