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 study of the human psyche has elucidated a bipartite structure of logic reflecting the quantum--classical nature of the world. Accordingly, we posited an approach toward studying the brain by means of the quantum--classical dynamics of a mixed Weyl symbol. The mixed Weyl symbol can be used to describe brain processes at the microscopic level and, when averaged over an appropriate ensemble, can provide a link to the results of measurements made at the meso and macro scale. Within this approach, quantum variables (such as, for example, nuclear and electron spins, dipole momenta of particles or molecules, tunneling degrees of freedom, and so on) can be represented by spinors, whereas the electromagnetic fields and phonon modes can be treated either classically or semi-classically in phase space by also considering quantum zero-point fluctuations. Quantum zero-point effects can be incorporated into numerical simulations by controlling the temperature of each field mode via coupling to a dedicated Nos\'e-Hoover chain thermostat. The temperature of each thermostat was chosen in order to reproduce quantum statistics in the canonical ensemble. In this first paper, we introduce a general quantum--classical Hamiltonian model that can be tailored to study physical processes at the interface between the quantum and the classical world in the brain. While the approach is discussed in detail, numerical calculations are not reported in the present paper, but they are planned for future work. Our theory of brain dynamics subsumes some compatible aspects of three well-known quantum approaches to brain dynamics, namely the electromagnetic field theory approach, the orchestrated objective reduction theory, and the dissipative quantum model of the brain. All three models are reviewed.

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.

This study investigates the effects of subclinical hypothyroidism and BDNF on telomere length in T1DM mothers and their neonates. Methods: In this prospective cohort study, 70 pregnant women with T1DM were enrolled. Subclinical hypothyroidism during the first trimester was characterized by elevated thyroid-stimulating hormone (TSH) levels ranging from 2.5 to 5.0mIU/L alongside normal free thyroxine (FT4) concentrations. Participants were stratified into two groups based on TSH levels: a maternal subclinical hypothyroid group (SHG, n=35) and a maternal euthyroid group (ETG, n=35). Leukocyte telomere length (LTL) measurements were conducted using whole blood samples from the mothers and umbilical veins. Results: The maternal LTL mean was 1.7 (SD=1.1), which was significantly shorter than the neonatal telomeres, with a mean of 2.3 SD (1.2). A significant correlation was observed between maternal and neonatal LTL (r=0.750, p<0.001). A positive association was found between neonatal LTL and BDNF levels in maternal circulation [β=0.421 (95% CI 0.536; 1.873; p=0.001)]. Neonatal LTL was negatively associated with gestational weight gain [β=-0.266 (95% CI-0.138; -0.009)], and with TSH in the first trimester [β=-0.237; (95% CI -0.493; - 0.010)]. Notably, neonates in the SHG exhibited shorter LTL, with a mean of 2.1 (1.0), compared to those in the ETG, who had a mean LTL of 2.7 (1.4). A positive association was found between maternal LTL and BDNF levels in maternal circulation [β=0.523 (95% CI 0.790; 1.950; P<0.001)]. Maternal LTL was negatively associated with gestational weight gain [β=-0.259 (95% CI -0.122; -0.010)], and with TSH in the first trimester [β=-0.231; (95% CI -0.422; - 0.015)]. Conclusions: Genetic factors affect neonatal LTL. Maternal subclinical hypothyroidism reduces neonatal LTL. The link between maternal and neonatal LTL and BDNF reveals the complex endocrine-neurotrophic interaction in T1DM telomere dynamics.

Modeling brain dynamics to better understand and control complex behaviors underlying various cognitive brain functions are of interests to engineers, mathematicians, and physicists from the last several decades. With a motivation of developing computationally efficient models of brain dynamics to use in designing control-theoretic neurostimulation strategies, we have developed a novel data-driven approach in a long short-term memory (LSTM) neural network architecture to predict the temporal dynamics of complex systems over an extended long time-horizon in future. In contrast to recent LSTM-based dynamical modeling approaches that make use of multi-layer perceptrons or linear combination layers as output layers, our architecture uses a single fully connected output layer and reversed-order sequence-to-sequence mapping to improve short time-horizon prediction accuracy and to make multi-timestep predictions of dynamical behaviors. We demonstrate the efficacy of our approach in reconstructing the regular spiking to bursting dynamics exhibited by an experimentally-validated 9-dimensional Hodgkin-Huxley model of hippocampal CA1 pyramidal neurons. Through simulations, we show that our LSTM neural network can predict the multi-time scale temporal dynamics underlying various spiking patterns with reasonable accuracy. Moreover, our results show that the predictions improve with increasing predictive time-horizon in the multi-timestep deep LSTM neural network.

Abstract

The pursuit of understanding the brain’s complex mechanisms is at the forefront of neuroscience, especially in developing early diagnostic tools for neurological diseases. Advances in neural fields, brain dynamics, and the integration of applied physics have opened new possibilities for identifying biomarkers indicative of neurological conditions such as Alzheimer’s disease, schizophrenia, and ADHD. Each of these fields contributes uniquely: neural fields offer a spatially distributed model of brain activity, brain dynamics provide insights into temporal patterns and oscillations, and applied surface physics enhances the precision of neural interface technologies and imaging. Combined, they form a multidisciplinary foundation that allows researchers to study the brain’s intricate structures and functions with unprecedented clarity, revealing potential pathways for diagnosing and treating neurological disorders.

This study assesses the predictive performance of six machine learning models in forecasting tumor dynamics within three months following Gamma Knife Radiosurgery (GKRS) in 77 brain metastasis (BM) patients. The analysis meticulously evaluates each model before and after hyperparameter tuning, utilizing accuracy, AUC and other metrics derived from confusion matrices. Initial findings highlighted that XGBoost significantly outperformed other models with an accuracy of 0.95 and an AUC of 0.95 before tuning. Post-tuning, the Support Vector Machine (SVM) demonstrated the most substantial improvement, achieving an accuracy of 0.98 and an AUC of 0.98. Conversely, XGBoost showed a decline in performance after tuning, indicating potential overfitting. The study also explores feature importance across models, noting that features like “control at one year”, “age of the patient”, and “beam on time for volume V1 treated”, were consistently influential across various models, albeit their impacts were interpreted differently depending on the model’s underlying mechanics. This comprehensive evaluation not only underscores the importance of model selection and hyperparameter tuning but also highlights the practical implications in medical diagnostic scenarios, where the accuracy of positive predictions can be crucial.

We derive time evolution equations, namely the Schrodinger-like equations and the Klein-Gordon equations for coherent fields and the Kadanoff-Baym (KB) equations for quantum fluctuations, in Quantum Electrodynamics (QED) with electric dipoles in 2 + 1 dimensions. Next we introduce a kinetic entropy current based on the KB equations in the 1st order of the gradient expansion. We show the H-theorem for the Leading-Order self-energy in the coupling expansion (the Hartree-Fock approximation). We show a conserved energy in the spatially homogeneous systems in the time evolution. We derive aspects of the super-radiance and the equilibration in our single Lagrangian. Our analysis can be applied to Quantum Brain Dynamics, that is QED with water electric dipoles. The total energy consumption to maintain super-radiant states in microtubules seems to be within the energy consumption to maintain the ordered systems in a brain.

Our brain continuously interacts with the body as we engage with the world. Although we are mostly unaware of internal bodily processes, such as our heartbeats, they may be influenced by and in turn influence our perception and emotional feelings. While there is a recent focus on understanding cardiac interoceptive activity and interaction with brain activity during emotion processing, the investigation of cardiac-brain interactions with more ecologically valid naturalistic emotional stimuli is still very limited. We also do not understand how an essential aspect of emotions like context familiarity influences affective feelings and is linked to cardiac-brain interactions. Hence to answer these questions, we designed an exploratory study by recording ECG and EEG signals for the emotional events while participants were watching emotional movie clips. Participants also rated their familiarity with the stimulus on the familiarity scale. Linear mixed effect modelling was performed in which the ECG power and familiarity were considered as predictors of EEG power. We focused on three brain regions, including prefrontal (PF), frontocentral (FC) and parietooccipital (PO). The analyses showed that cardiac-brain interaction is dependent on familiarity such that the interaction is stronger with high familiarity. In addition, the results indicate that arousal is predicted by cardiac-brain interaction, which also depends on familiarity. The results support emotional theories that emphasize context dependency and interoception. Multimodal studies with more realistic stimuli would further enable us to understand and predict different aspects of emotional experience.

This study investigates the comparative performance of autoencoders and traditional machine learning (ML) algorithms in predicting tumor dynamics following Gamma Knife radiosurgery (GKRS) for brain metastases (BMs). The research retrospectively analyzed clinical data from 77 patients (median age: 64 years; 45 males, 32 females) treated at the “Prof. Dr. NicolaeOblu” Emergency Clinic Hospital-Iasi. The dataset comprised 12 variables, including socio-demographic, clinical, treatment, and radiosurgery-related factors. The primary outcome was tumor progression or regression within three months post-GKRS, with 71 cases of regression and 6 cases of progression observed. Traditional ML models—Logistic Regression, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Extra Trees, Random Forest, and XGBoost—were evaluated, achieving accuracy rates ranging from 0.91 (KNN) to 1.00 (Extra Trees). When incorporating features extracted by autoencoders, the performance of these models generally improved, especially with compression in the bottleneck layer. For instance, Logistic Regression's accuracy increased from 0.91 to 0.94, while SVM's accuracy improved significantly from 0.85 to 0.96. XGBoost consistently performed well across both traditional and hybrid setups, maintaining an accuracy of 0.94 with an AUC of 0.98. The findings suggest that hybrid approaches combining deep learning with traditional ML techniques can significantly enhance predictive accuracy and robustness, particularly in the context of GKRS for BMs. This improved performance has potential implications for more informed clinical decision-making in personalized medicine.

Consciousness is a special type of interaction between subjects exchanging by lingua quanta (phonemes). A set of lingua quanta composes a thesaurus placed on the edge of chaos. Its library is a memory, modification of which is due to tuning of memristive neural elements scattered in the brain volume. The memristive neural model takes into consideration two types of neurons - excitatory and inhibitory and the current leakage, all at the body temperature, T = 309 K. At such temperatures only heavy ions like hydrogen ions - protons can pass robustly through the water medium of the brain. The robust ion transport is proton water wires supported by the Grotthuss mechanism. Final aims of the ions are the gap junctions (electric synapses) linking nearest neurons. Following these observations, a model of excitable nervous tissue is constructed. Namely, a difference mapping on the basis of sigmoid curves can reproduce chaotic modes of neural activity proved by positive values of the Lyapunov exponent. The edge of chaos is placed near the bifurcation boundary dividing the chaos and the periodic convulsive activity typical at the epileptic discharges. In this region the self-sustained spiral waves occur. An intermittent activity of the competing excitatory and inhibitory neurons is observed on the edge of chaos. The intermittent electrical activity of neural tissues is demonstrated by records both from different literature issues and records made by the author together with DR. A. Dudkin on slices of CA1 field of the hippocampus.

Based on non-invasive neuroimaging techniques and graph theory-based network analyses, many researchers have tried to use small-world network model to elucidate sex differences in the brain. This manuscript aims to compile the related research findings from the past few years and summarize the sex differences in human brain networks from the perspective of small-world properties. We reviewed published reports examining altered small-world properties in both the functional and structural brain networks between males and females. Based on four patterns of altered small-world properties proposed--randomization, regularization, stronger small-worldization and weaker small-worldization, we found that current results point to a significant trend toward more regularization in females and more randomization in males in the functional brain networks. As for particular topological properties, the most consistent findings include a significant shift toward higher global efficiency in males and higher local efficiency in females in the functional network studies. On the other hand, there seems to be no consensus to date on the sex differences in small-world properties of the structural brain networks. Nevertheless, we noticed that the sample sizes in many published studies are limited, and future studies with larger samples are warranted to obtain more reliable results. We anticipate that the conclusions in this manuscript will contribute to a deeper understanding of neurobiological mechanisms underlying the sex differences in the brain.

Whole-brain radiation therapy and stereotactic radiosurgery are two treatment modalities commonly utilized to treat brain metastases (BMs). The aim of this study is to retrospectively analyze the main radio-oncologic and clinical-demographic aspects of a cohort of BM patients treated with Volumetric Modulated Arc Therapy for radiosurgery (VMAT-RS). This is a cross-sectional observational design study with retrospective review of medical records of patients with brain metastases treated with VMAT- RS between 2012 and 2018. Clinical and demographic data, with special attention to sex, age, primary tumor, brain tumor-related epilepsy (BTRE), number and brain location of BMs, Karnofsky Performance Status (KPS), the updated DS-GPA prognostic index and the survival estimated according to the Kaplan-Meier model from the date of radiosurgery were analyzed. One hundred and twenty-one patients with 229 BMs were treated with VMAT-RS. Patients presented 1-4 BMs, which were treated with 5 non-coplanar VMAT arcs. Sixty-eight percent of the patients had lung cancer and 35% of the BMs were in the frontal lobe. Proportion of local control was 88.5%. BTRE prevalence was 30.6%. The median survival time (MST) was 7.7 months. In the multivariate analysis of the Cox Regression model KPS70 (HRKPS<70=2.59; p=0.001) and higher DS-GPA (HRDS-GPAII =0.55, p=0.022; HRDS-GPAIII-IV =0.38, p=0.006) were associated with improved survival. In the univariate analysis, primary tumor, age and the presence of metastases in the posterior fossa (PFBMs) were also significative. In conclusion, the VMAT-RS is a technique with an overall survival comparable to other radiosurgery techniques. The median survival is significantly longer in those with higher KPS and DS-GPA. Other variables such as the type of primary tumor, age and PFBMs could also influence survival, although further studies are needed.

Traumatic Brain Injury (TBI) remains a leading cause of morbidity and mortality among all ages; despite the advances, understanding pathophysiological responses after TBI is still complex, involving multiple mechanisms. Previous reviews have focused on potential targets; however, the research on potential targets has continuously grown in the last five years, bringing even more alternatives and elucidating previous mechanisms. Knowing the key and updated pathophysiology concepts is vital for adequate management and better outcomes. This article reviews the underlying molecular mechanisms, the latest updates, and future directions for pathophysiology-based TBI management.

Intracortical microelectrodes that can be implanted have the ability to capture fast-changing neuron action potentials in the living brain. Despite this potential, many obstacles must still be overcome for reliable, long-term, high-quality recordings and accurate analysis of brain activity. These challenges include improving recording quality, enhancing recording stability, increasing recording capacity, and adding multi-functional features. One potential approach to enhance implantable microelectrodes involves the advancement of materials, refinement of implantation methodologies, and augmentation of the number of sites for recording. However, these challenges are still being actively researched, and advancements in microelectrode technology are underway. The difficulties with implantable microelectrodes are evaluated, and solutions are presented from different perspectives. The latest advancements in microelectrode technology are reviewed and condensed, and future possibilities are explored.

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: Patients undergoing brain tumor resection experience neurological and cognitive (i.e., neurocognitive) changes reflected in altered performance on neuropsychological tests. These changes can be difficult to explain or predict. Brain connectivity, measured with neuroimaging, offers one potential model for examining these changes. In this study, we evaluated whether longitudinal changes in brain connectivity correlated with changes in neurocognitive abilities in patients before and after brain tumor resection. Methods: Patients underwent functional and diffusion MR scanning and neuropsychological evaluation before tumor resection followed by repeat scanning and evaluation two weeks post-resection. Using this functional and diffusion imaging data, we measured changes in the topology of the functional and structural networks. From the neuropsychological testing scores, we derived a composite score that described a patient’s overall level of neurocognitive functioning. We then used a multiple linear regression model to test whether structural and functional connectivity measures were correlated with changes in composite scores. Results: Multiple linear regression on 21 subjects showed that connectivity changes were highly correlated with changes in neuropsychological evaluation scores (R² adjusted = 0.79, p<0.001). Changes in functional local efficiency (p<0.001) and global efficiency (p<0.05) were inversely correlated with changes in composite score, while changes in modularity (p<0.01) as well as the patient’s age (p<0.05) were directly correlated with changes in composite score. Conclusion: Short interval changes in brain connectivity markers were strongly correlated with changes in the composite neuropsychological test scores in brain tumor resection patients. Our findings support the need for further exploration of brain connectivity as a biomarker relevant to brain tumor patients.

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.

Brain tumors still remain a deadly cancer that, in most cases, is difficult to diagnose at an earlier stage. Therefore, it is necessary to develop rapid, sensitive methods for detecting cancer biomarkers. Such a biomarker may be a microRNA which expression level in body fluids is strongly correlated with cancer. Numerous studies have demonstrated changes in the expression of microRNAs in cerebrospinal fluid and blood samples collected from patients with brain tumors. These new biomarkers have the potential to help diagnose brain cancers at an early stage, avoiding the most invasive procedures. This review discusses the functional role of microRNAs and the prospects for their use as diagnostic biomarkers in patients with brain tumors.

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.

Background: Dosimetric predictors of brain necrosis (BN) have not yet been established for fractionated stereotactic radiotherapy (SRT). Methods: Multivariate logistic models were developed for comprehensive analyses of dosimetric predictors in patients who received first-line fractionated SRT for brain metastases (BMs). The normal brain volume receiving a xx Gy biological dose in 2 Gy fractions (VxxGyE) was calculated from the retrieved dose-volume parameters. Results: Three-fraction SRT was delivered to 34 patients with 74 BMs (mean target volume, 4.3 cc), 5-fraction SRT to 58 with 106 BMs (15.4 cc), and 10-fraction SRT to 20 with 35 BMs (25.9 cc) according to protocols depending on the target volume (p &lt;0.001). In the 5- and 10-fraction groups, the incidence of symptomatic BN was significantly higher in patients with a larger V50GyE (odds ratio: 1.07, p &lt;0.02), V55GyE (1.08, p &lt;0.01), or V60GyE (1.09, p &lt;0.01). The incidence of BN was also significantly higher in cases with V55GyE &gt;30 cc or V60GyE &gt;20 cc (p &lt;0.05). Conclusion: In 5- or 10-fraction SRT, at least V55GyE ≤30 cc or V60GyE ≤20 cc should be maintained to lower the risk of BN.

The blood-brain barrier (BBB) acts as a specialized structure separating the brain from peripheral blood circulation and plays an important role in brain function. Following an ischaemic stroke or cerebral ischaemia, the BBB is damaged leading to degraded proteins being released into blood circulation. However, little is known about cerebral ischaemia and reperfusion (I/R) induced BBB damage and changes in circulatory biomarkers. This study aims to use both immunohistochemistry and western blotting (WB) to examine neuronal death, glial cell alterations and changes in BBB tight junction (TJ) proteins such as zonula occludens-1 (ZO-1), Occludin and Claudin-5 in the hippocampus in a murine model of cerebral I/R. The changes in these proteins in the blood serum of this model were assessed by enzyme-linked immunosorbent assay. The results showed neuronal death and a significant increase in glial fibrillary acidic protein (GFAP), a protein primarily expressed in astrocytes and a significant decrease in TJ proteins, ZO-1, Occludin and Claudin-5 in the hippocampus of occluded mice as compared to sham-operated mice. These changes are associated with an increased level of these proteins in blood serum in ischaemic mice, suggesting that these proteins can be used as potential biomarkers for determining ischaemic stroke.

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.

Epilepsy is a neurological disorder that affects approximately 1% of the world's population. To diagnose and estimate the occurrence of epilepsy, the analysis of recorded brain activity is performed by a neurologist, which is not only time-consuming and tedious but also occasionally accompanied by human error. Therefore, in recent decades, researchers have aimed to unravel an approach for designing and building an automated method for diagnosing and estimating the occurrence of epilepsy. Accordingly, the present study proposed two new-fangled ways based on brain signals and a convolutional neural network (CNN). Moreover, this research implements a CNN with a sequential three-layer structure. Numerous experiments were performed, and the accuracy of estimating epilepsy using the developed methods was achieved at 95% without feedback and 97% with feedback. The proposed methods were proven to be more accurate than the previous techniques and can be employed as a physician's assistant once entering the field of operation.

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.

In Orch OR model ; using electromagnetic fields, the brain captures, stores and analyzes the information of the cells and then sends the necessary commands to them. If the cells undergo changes and become cancer cells, the information stored in the brain and the electromagnetic signals inside and outside it change. Based on these changes, tumor and cancer formation can be detected in the early stages, and by storing the right information in the brain; it created the context for sending appropriate messages to return the cells to a normal state.

Introduction: Adverse events related to vaccines are reactions that can lead to serious complications, in the present that we live at the publication of this article with the need to generate high rates of vaccination have been presented in the case of vaccine agents against COVID-19 adverse events, with thrombotic events being the most important. Case Presentation: This is a 37-year-old female patient who presents 11 days after ChAdOx1-S vaccination against COVID-19 presents with intense headache associated with symptoms of intracranial hypertension, she was initially taken to simple cranial tomography showing presence of cerebral edema and indirect signs of cerebral venous thrombosis, it is proposed to carry out cerebral angiography which showed the presence of thrombosis of both transverse venous sinuses, no hypercoagulability states were found in the laboratories, the immunological tests carried out for antiphospholipid syndrome were negative, the thrombotic event was associated with the ChAdOx1-S vaccine, later the patient was taken to thrombectomy by Neuroradiology, achieving complete channeling of both transverse venous sinuses. Conclusions: Adverse events associated with vaccination have been described with multiple vaccine agents, this component against COVID-19 is also an event to consider, knowing the pathophysiology of these events is essential to be able to reduce these risks and select the least risky agent. Despite this risk, vaccination remains the only cost-effective measure to reduce the morbidity and mortality associated with COVID-19.

Brain magnetic resonance imaging (MRI) offers a unique lens to study neuroanatomic support of human neurocognition and intelligence. A core mystery is the MRI explanation of individual differences in neurocognition and intelligence. The past four decades have seen great advancement in studying this century-long mystery, but the sample size and population-level studies limit the explanation at the individual level. The recent rise of big data and artificial intelligence offers novel opportunities. Yet, data sources, harmonization, study design, and interpretation need to be carefully considered. This review aims to summarize past work, discuss rising opportunities and challenges, and facilitate further investigations on machine intelligence inferring human intelligence.

Background: Traumatic brain injury (TBI) remains a significant risk factor for post-traumatic epilepsy (PTE). The pathophysiological mechanisms underlying the injury-induced epileptogenesis are under under investigation. The dentate gyrus, a structure highly susceptible to injury, and has been implicated in the evolution of seizure development. Methods: Utilizing the murine unilateral focal control cortical impact (CCI) injury, we evaluated seizure onset using 24/7 EEG video analysis at 2-4 months post-injury. Cellular changes in the dentate gyrus and hilus of the hippocampus were quantified by non-biased stereology and Imaris image analysis to evaluate Prox1-positive cell migration, astrocyte branching and morphology, as well as neuronal loss at four months post-injury. Isolation of region-specific astrocytes and RNA-seq was performed to determine differential gene expression in PTE+ vs. PTE- that may comport with the epileptogenic process. Results: CCI injury resulted in 37% PTE+-incidence, which increased with injury severity and hippocampal damage. Histological assessments uncovered a significant loss of hilar interneurons that coincided with aberrant migration of Prox1-positive granule cells and reduced astroglial branching in PTE+ compared to PTE- mice. We uniquely identified Cst3 as a PTE+-specific gene signature in astrocytes across all brain regions. Conclusions: These findings suggest that epileptogenesis may emerge following TBI due to distinct aberrant cellular remodeling events and key molecular changes in the dentate gyrus of the hippocampus.

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.

Exergames (EG) are interactive video games that require physical activity and use gamification to make exercise more engaging. EG interventions have shown various benefits for older adults, such as improved mental health, quality of life, and reduced fall risk. Enhanced cognition is thought to drive these benefits. This review aimed to identify neural correlates underlying cognitive improvements in healthy older adults and those with neurocognitive disorders. We systematically searched major databases and included 13 studies from 2,095 records. Findings revealed that EG interventions led to structural brain changes and improved functional connectivity in healthy adults, Parkinson patients, and those with mild cognitive impairment (MCI). Increased activity in the frontal, temporal, and precuneus regions during rest was specific to adults with neurocognitive disorders. Neuroplastic changes, such as elevated BDNF levels and increased neurovascular coupling, were observed in both groups. However, methodological limitations in some studies highlight the need for further high-quality research.

Traumatic Brain Injury represents a significant public health concern due to its role in traumatic death and disability, often caused by head impacts or rapid accelerations. Despite advancements in Finite Element Head Models, existing models primarily represent adult males, neglecting anatomical and physiological differences between genders and age groups. Additionally, the mechanistic roles of specific intracranial tissues, such as the dura mater, have conventionally been overlooked. To better understand the mechanical behavior of the brain and its injured regions in the context of TBI, including the dura mater, this study proposes the development of a Female Finite Element Head Model. This model, representative of a middle-aged female subject, was developed using medical image-derived geometry and finite element modeling techniques. The validation results demonstrate a similarity between the numerical displacement curves and those obtained experimentally. In the model with dura mater, the numerical results show analogous behavior to the experimental results, despite minimal variations in the amplitude of the curves. These advancements highlight the significance of including the dura mater in biomechanical brain modeling. Incorporating the dura mater in Finite Element Head Models produces more realistic results than models without it. This emphasizes the importance of enhancing biomechanical models to better represent anatomical complexity.

Extracellular vesicles (EVs), including exosomes, microvesicles, and other lipid vesicles derived from cells, play a pivotal role in intercellular communication by transferring information between cells. EVs secreted by progenitor and stem cells have been associated with the therapeutic effects observed in cell-based therapies, and they also contribute to tissue regeneration following injury, such as in orthopedic surgery cases. This review briefly explores the involvement of EVs in tissue repair and nerve regeneration, their potential as drug carriers, and their significance in stem cell research and cell-based therapies. It underscores the importance for bioengineers to comprehend and manipulate EV activity to optimize the efficacy of tissue engineering and regenerative therapies.

The abnormal accumulation of cells in the human brain, if left untreated, may cause brain damage. Management and treatment of these tumours require an early and accurate diagnosis, while their prognostic characterisation can also be beneficial in the choice of care planning for the patient. CDSSs are being continuously developed and integrated into routine clinical practice as they assist clinicians and radiologists to deal with an enormous amount of medical data, reduce clinical errors, and improve diagnostic capabilities. They assist detection, classification, and grading of brain tumours as well as alerting physicians of requirement of change in treatment plans. The aim of this systematic review is to identify various CDSSs used in brain tumour diagnosis and prognosis, that rely on data captured by any imaging modality. Based on the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, the literature search was conducted in PubMed and Engineering Village Compendex databases. This review examines various CDSS tool types, system features, techniques used, accuracy, and outcome, to provide the latest evidence available in the field of neuro-oncology. An overview of different types of CDSSs used to support clinical decision-making in the management and treatment of brain tumours, along with highlighting their benefits, challenges, and future perspectives has been provided.

The appearance of brain metastasis is the most serious complication of breast cancer with mostly fatal outcomes. To reach the brain, tumor cells need to pass the blood-brain barrier (BBB). The molecular mechanisms underlying penetration of the BBB are largely unknown. Previously we found that tumor-infiltrating T lymphocytes enhance the development of brain metastasis of estrogen receptor-negative (ER-) breast cancer. In the current study, we investigate the contribution of T lymphocytes and the IFN- pathway in enabling breast cancer cells to pass the in vitro BBB. CD8+ cells display the strongest stimulatory effect on breast cancer cell passage. We show that inhibition of the IFN- receptor in MDA-MB-231 breast cancer cells, or neutralization of soluble IFN-, impairs the in vitro trespassing of breast cancer cells. Importantly, we validated our findings using gene expression data of breast cancer patients. CXCL-9,-10,-11/CXCR3 axis, dependent on IFN- signaling activity, was overexpressed in primary breast cancer samples of patients who developed brain metastasis. The data support a role for T-lymphocytes and the IFN- pathway in the formation of brain metastasis of ER- breast cancer, and offer targets to design future therapies for preventing breast cancer cells to cross the BBB.

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.

Human language and social cognition are two key disciplines that have traditionally been studied as separate domains. However, emerging research from detailed studies of comparative animal behavior, human social behavior, language acquisition in children, social cognitive neuroscience, and the cognitive neuroscience of language suggest that language and social cognition are two deeply interrelated capacities of the human species. For instance, recent developmental studies on the acquisition of language in infants and young children, draw attention to the important crucial benefits associated with several different aspects of social stimulation for youngsters, including the quantity and quality of linguistic input, dyadic infant/child-to-parent verbal and non-verbal social interactions, and other important social cues integral for facilitating language learning and social bonding. Studies of the adult human brain further suggest a high degree of specialization for sociolinguistic information processing, memory retrieval, and comprehension, suggesting the function of these regions may link language with social cognition and social bonding. In effect, the social brain and social complexity hypotheses may jointly help to explain how neurotypical children and adults learn language, why autistic adults and children exhibit simultaneous deficits in language and social cognition, and why nonhuman primates and other animals with significant computational abilities do not acquire the capacity for language. But perhaps most critically, the following article argues that this and related research will allow scientists to generate a holistic profile and deeper understanding of the healthy adult social brain, while developing more innovative and effective diagnoses, prognoses, and treatments for maladies and deficits also associated with the social brain.

The question of what generates conscious experience has mesmerized thinkers since the dawn of humanity, yet its origins remain a mystery. The topic of consciousness has gained traction in recent years, thanks to the development of large language models that now arguably pass the Turing test, an operational test for intelligence. However, intelligence and consciousness are not related in obvious ways, as anyone who suffers from a bad toothache can attest - pain generates intense feelings and absorbs all our conscious awareness yet nothing particularly intelligent is going on. Still, in the hard sciences, this topic is frequently met with skepticism because to date no protocol to measure the content or intensity of conscious experiences in an observer-independent manner has been agreed upon. Here we present a novel proposal: Conscious experience arises whenever a quantum mechanical superposition forms. Our proposal has several implications: First, it suggests that the structure of the superposition determines the qualia of the experience. Second, quantum entanglement naturally solves the binding problem, ensuring the unity of phenomenal experience. Finally, a moment of agency may coincide with the formation of a superposition state. We outline a research program to experimentally test our conjecture via a sequence of quantum biology experiments. Applying these ideas opens up the possibility of expanding human experience through brain-quantum computer interfaces.

Brain models present a viewpoint on the fundamental structural components of the brain and their mutual organization, generally relative to a particular concept of the brain axis. A model may be based on adult brain structure or on developmental morphogenetic aspects. Brain models usually have functional implications, depending on which functional properties derive from the postulated organization. This essay examines the present scenario about brain models, emphasizing the contrast between columnar or other longitudinal models and transverse subdivisional neuromeric models. In each case, the main functional implications and apparent problems are explored and commented. Particular attention is given to the modern molecularly based ‘prosomeric model’, which postulates a set of 20 transverse prosomeres as the developmental units that serve to construct all the cerebral parts and the particular typology of many different neuronal populations within the forebrain and the hindbrain, plus a number of additional spinal cord units. These metameric developmental units (serially repeated, but with unique molecular profiles) confer to this model remarkable functional properties based mainly on its multiplicity and modularity. Many important brain functions can be decomposed into subfunctions attended to by combined sets of neuronal elements derived from different neuromeres. Each neuromere may participate in multiple functions. Most aspects related to creation of precise order in neural connections (axonal navigation and synaptogenesis) and function is due to the influence of neuromeric anteroposterior and dorsoventral positional information. Research on neuromeric functionality aspects is increasing significantly in recent times.

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

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.

Brain metastasis is a severe and complicated cancer that requires timely screening and follow-up approaches using precise segmentation techniques for effective surgical intervention, radiation therapy, or monitoring the disease progression. In this study, we explore the efficacy of transfer learning in improving the automatic segmentation of brain metastases on Magnetic Resonance Imaging scans with the subsequent possibility of using it in clinical practice for preventive examinations and remote diagnostics. We train three deep learning models on a public dataset from the Brain Tumor Segmentation 2024 Challenge, then fine-tune these pretrained models on a small private dataset and compare them to models trained on private data from scratch. The results indicate that models utilizing transfer learning achieve superior accuracy and generalization in segmenting brain metastases. We also observed that the custom loss function significantly enhances performance compared to the default configuration. This study highlights the importance of leveraging transfer learning in medical imaging to address challenges associated with small, specialized datasets.

Cancer ranks second among the causes of mortality worldwide,following cardiovascular diseases.Brain cancer, in particular, has lowest survival rate of any kind of cancer. Brain tumours vary in their morphology, texture, and location, which determine their classification. Accurate diagnosis of the tumour category enables physicians to select optimal treatment strategies and potentially prolong patients’ lives. Researchers who also implemented deep learning models for diagnosing diseases in recent years largely focused on deep neural network optimization to enhance neural network performance. This implicates implementing models with the best performance and incorporating various network architectures by configuring their hyperparameters. This paper presents a novel hybrid approach method for improved brain tumour classification by combining CNN and EfficientNetV2B3 as feature extraction, followed by (KNN) for classification. To evaluate the recommended method’s efficacy, two widely known benchmark MRI datasets were utilized in the experiments. The initial dataset consisted of 3064 MRI images depicting meningiomas,pituitary,and gliomas tumours.Images from two classes of normal brain and brain tumour were included in the second dataset, which was obtained from Kaggle.In order to enhance performance even more, the study concatenates the CNN and EfficientNetV2B3 flattened outputs before feeding them into the KNN classifier. The proposed framework run on two different dataset and demonstrates outstanding performance with an accuracy of 99.51% and 99.8% on each dataset.

Background and Purpose: Oxidative stress is an important factor in the pathogenesis of neurological problems. One of the compounds causing oxidative stress is diazinon. In the present project, the protective role of gallic acid compound in reducing oxidative stress in brain tissue of mice exposed to diazinon was investigated. Method: In this study, eight groups of six series of mice including the first group (control) of normal saline, the second group of diazinon (40 kg/mg) as IP, three groups of diazinon with gallic acid (50, 100, 200 kg/mg), was prescribed as a single dose and for 24 hours. The atropine + pralidoxime group was also evaluated as a standard treatment group. At 24 hours after the last dose, the animals were sacrificed and brain tissue was examined to assess oxidative stress parameters, including glutathione content, protein carbonyl content, lipid peroxidation, reactive oxygen species (ROS) and mitochondrial function in mitochondria isolated from brain tissue. Results: The results of this research showed that oxidative stress biomarkers increased significantly (P<0.001) in the diazinon group compared to the control group. Oxidative stress was significantly reduced in the groups receiving gallic acid at a dose of 200 and 100 kg/mg of diazinon compared to the diazinon group. Conclusion: The results of the present study show that diazinon causes damage to brain tissue by inducing oxidative stress. Therefore, according to the reduction of oxidative stress by gallic acid compound, it can be concluded that this compound can protect against brain toxicity caused by diazinon in animal model by stimulating antioxidant and radical scavenging pathways.

Background and aims: Brain metastases are prevalent in the late stages of malignant melanoma. Multimodal therapy remains challenging. Patient-derived organoids (PDOs) represent a valuable pre-clinical model, faithfully recapitulating key aspects of the original tumor, including the heterogeneity and the mutational status. This study aimed to establish PDOs from melanoma brain metastases (MBM-PDOs) and to test the feasibility of using them as a model for in vitro targeted-therapy drug testing.Methods: Surgical resection samples from eight patients with melanoma brain metastases were used to establish MBM-PDOs. Samples were enzymatically dissociated followed by seeding into low-attachment plates to generate floating organoids. The MBM-PDOs were characterized genetically, histologically, immunohistologically and compared with the parental tissue. The MBM-PDO cultures were exposed to dabrafenib (BRAF inhibitor) and trametinib (MEK inhibitor) followed by cell viability assessment.Results: Seven out of eight cases were successfully cultivated, maintaining the histological, immunhistological phenotype, and the mutational status of the parental tumors. Five out of seven cases harbored BRAF V600E mutations and were responsive to BRAF and MEK inhibitors in vitro. Two out of seven cases were BRAF wild type, one case harboring an NRAS mutation and the other harboring a KIT mutation, and both were resistant to BRAF and MEK inhibitor therapy. Conclusion:We successfully established PDOs from melanoma brain metastases surgical specimens, which exhibited a consistent histological and mutational profile with the parental tissue. Using FDA-approved BRAF and MEK inhibitors, our data demonstrates the feasibility of employing MBM-PDOs for targeted-therapy in vitro testing.

Despite impressive progress in quantum biology, many questions about perception, cognition, memory, and their relation to processing of information remain unanswered. Here is an attempt to draw a unified picture starting with the basic quantum-mechanical phenomenon of nano-superconductivity in the microtubules and extending it to quantum processing of information, and generation of coherent Josephson radiation. A model for the generation in the axons of neurons is suggested. Like in a symphony, but on frequencies ten orders of magnitude higher, the radiation forms resonant standing electromagnetic waves, which are defined by the anatomy, synchronize all the functions in organism, and are behind the memory, perception, and cognition of a living being. It is true that we are made of atoms, but we are coherent electromagnetic waves.

Oligodendroglioma (OG) is a brain tumor that contributes to < 1% of brain tumor diagnoses in the pediatric population. Unfortunately, pediatric OG remains without definitive molecular characteristics to aid in diagnosis, and little is known about the tumor microenvironment. Tumor cells' metabolism and proliferation rate are generally higher than healthy cells, so their iron demand is also significantly increased. This consideration underlines the great importance of iron for tumor development and progression. In this context, this study aims to evaluate the effect of iron in a cellular in vitro model of human oligodendroglioma brain tumor. Cell morphology, the effect of siderotic medium on cell growth, iron uptake, and the expression of iron metabolism-related genes were evaluated by optic microscopy, ICP-MS, confocal microscopy, and RealTime PCR, respectively. This study underlines the great importance of iron for tumor development and progression, but also the possibility of reducing the available iron concentration to determine an antiproliferative effect on OGs. Therefore, every attempt can be promising to defeat the OGs for which there are currently no long-term curative therapies.

Brain capillary endothelial cell(s) (BECs) have numerous functions including their semipermeable interface-barrier (transfer and diffusion of solutes), trophic (metabolic homeostasis), tonic (vascular hemodynamics), and trafficking (vascular permeability, coagulation, and leukocyte extravasation) functions to provide brain homeostasis. BECs also serve as the brain’s sentinel cell of the innate immune system and are capable of antigen presentation. In metabolic syndrome (MetS) there are two regions resulting in proinflammatory signaling of BECs. Namely, visceral adipose tissue depots supplying excessive peripheral cytokines/chemokines (pCC) and gut microbiota dysbiotic regions supplying excessive soluble lipopolysaccharide (sLPS), small LPS-enriched extracellular vesicle exosomes (lpsEVexos), and pCC. This dual signaling of BECs at their receptor sites results in BEC activation and dysfunction (BECact/dys) and neuroinflammation. sLPS and lpsEVexos signal BECs toll-like receptor four, which then signals translocated nuclear factor kappa B (NFkB). Translocated NFkB promotes the synthesis and secretion of BEC proinflammatory cytokines and chemokines. Specifically, the chemokine CCL5 (RANTES) is capable of attracting microglia cells to BECs. BEC neuroinflammation activates perivascular space(s) (PVS) resident macrophages. Excessive phagocytosis by reactive resident PVS macrophages results in a stagnation-like obstruction, which along with increased capillary permeability due to BECact/dys could expand the fluid volume within the PVS to result in enlarged PVS (EPVS). Importantly, this remodeling may result in pre- and post-capillary EPVS that would contribute to their identification on T2-weighted MRI, which are considered to be biomarkers for cerebral small vessel disease.

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.

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.

Alzheimer’s disease (AD) is a predominant and incurable chronic debilitating neuro-degenerative disorder occupying more than 60% of all types of dementias. It is inaugurating by a cascade of events initiating from amnesic-type memory impairment and by gradually loss of cognitive and executive capacities, which is an intolerable problem for the patients and their familiars. Pathologically, there is overwhelming evidence that clumps of misfolded amyloid-β (Aβ) and hyperphosphorylated Tau protein aggregate in the brain. These pathological processes leading to synapse loss, neuronal loss, brain atrophy and gliosis culminating in neurodegeneration and fuelling AD. Thus, at a basic level, abnormality in brain proteins function is observed, causing disruption in the brain network and loss of neural connectivity. Nevertheless, AD is a multifactorial disorder, caused by a combination of age-related changes, genetic, environmental and lifestyle factors that affect the brain over time, its mysterious pathology seems non limited to senile plaques (Aβ) and neurofibrillary tangles (tau), but plethora of substantial and biological processes have been also emerged in its pathogenesis such as — breakdown and/or dysfunction of the blood–brain barrier (BBB); patients’ carriers of the gene variant APOE4; and the immunosenescence of the immune system. Furthermore, type 2 diabetes (T2DM) and metabolic syndrome (MS) whose have also observed as early markers that may provoke pathogenic pathways that lead or aggravate AD progression and pathology. Notwithstanding, of various pathological pathways, there are numerous substantial AD features that require shedding light on, such as chronic neuroinflammation, decrease glucose utilization and energy metabolism as well as brain insulin resistance (IR). Herein, we come to broadened our understanding & to connect the dots of the multiple comorbidities and their cumulative impact that may have synergistic effects on BBB dysfunction and AD pathology. We shed light on the path-physiological modifications in the cerebral vasculature that may contribute to AD pathology and cognitive decline prior to clinically detectable changes in amyloid beta (Aβ) and tau pathology, diagnostic biomarkers of AD, neuroimmune involvement and the role of APOE4 allele and AD-IR pathogenic link - the shared genetics and metabolomics biomarkers between AD and IR disorders. Investment in the future researches brings us closer to know the pathogenesis of AD, and paves the way to build preventive and treatment strategy.

Near-infrared spectroscopy (NIRS) has become a key modality in medical imaging, finding application in both brain and breast imaging. This paper discusses the current trends in NIRS for brain and breast imaging, exploring advances in multi-modal integration with modalities such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Challenges related to spatial resolution, depth sensitivity, and the impact of extracerebral tissues on signal specificity are examined. In addition, ongoing efforts to enhance hemodynamic measurements’ quantitative accuracy. Challenges, including limited spatial resolution and tissue heterogeneity, are discussed. The discussion extends to diffuse optical tomography and ongoing instrumentation development, clinical trials and studies validating NIRS diagnostic efficacy in breast imaging. The paper emphasizes the need for standardization, integration into routine clinical practice, and motivates for future work.

There is a growing interest in glial cells in the central nervous system due to their important role in maintaining brain homeostasis both under physiological conditions and after injury. A significant amount of evidence has been accumulated regarding their capacity to exert either pro-inflammatory or anti-inflammatory effects under different pathological conditions. In combination with their known proliferative potential, they contribute not only to the limitation of brain damage and tissue remodeling but also to neuronal repair and synaptic recovery. Moreover, reactive glial cells can modulate the processes of neurogenesis, proliferation, and migration of neurons in the existing neural circuits in the adult brain. By discovering precise signals within specific niches, the regulation of sequential processes in adult neurogenesis holds the potential to unlock strategies that can stimulate the generation of functional neurons, whether in response to injury or as a means of addressing degenerative neurological conditions. Cerebral ischemic stroke, a condition falling within the realm of acute vascular disorders affecting the circulation of the brain, stands as a prominent global cause of disability and mortality. Extensive investigations into glial plasticity and their intricate interactions with other cells in the central nervous system have predominantly relied on studies conducted on experimental animals, including rodents and primates. However, valuable insights have also been gleaned from in vivo studies involving post-stroke patients, utilizing highly specialized imaging techniques. Following the attempts to map brain cells, the role of various transcription factors in modulating gene expression in response to cerebral ischemia is gaining increasing popularity. Although the results obtained thus far remain incomplete and occasionally ambiguous, they serve as a solid foundation for the development of strategies aimed at influencing the recovery process after ischemic brain injury.

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.

Background: The practice of heading in soccer is widely recognized as an important aspect of the game both offensively and defensively, frequently implemented by players. However, concerns persist about the negative impact of this technique on players' cognitive function and symptoms, both in the short and long-term. This meta-review aims to systematically map the existing literature on soccer heading and its implications on the long-term effects; Methods: We conducted a meta-review of systematic reviews following PRISMA-ScR guidelines in PubMed, Embase and Web of Science databases. Searches were conducted between 21 February and 20 March 2024, in English, with a limitation to articles published between January 2000 and March 2024.; Results: Three systematic reviews were eligible for having addressed the subject of head-ball impacts in soccer and their physiological, neurological and cognitive impact. While most studies did not report any significant long-term changes, short-term impairments in memory and reaction time were observed in some instances, normalizing within 24 hours. Neurochemical markers showed mixed results, with increased NF-L levels persisting up to a month in certain cases. Visual reflexes and corticomotor inhibition also exhibited temporary dysfunctions post-heading; Conclusions: This meta-review highlighted the limited number of systematic reviews on the effects of heading in soccer in young and adult players. The current evidence suggests that while heading may lead to short-term cognitive and physiological changes, the long-term effects remain uncertain and probably under-studied. Further research, particularly with professional players and standardized methodologies on long-term follow-up, is needed to clarify these potential risks and inform safety measures in soccer.

Zika virus (ZIKV) impacts the developing brain. Here a technique was applied to define, in 3D, developmental changes in the brain of ZIKV-infected mice. Postnatal day 1 mice were uninfected or ZIKV-infected, then analysed by iodine staining and micro-CT scanning (diffusible iodine contrast enhanced micro-CT; diceCT) at 3-, 6- and 10-days post infection (dpi). Multiple brain regions were visualised using diceCT; olfactory bulb, cerebrum, hippocampus, midbrain, interbrain, and cerebellum, along with the lens and retina of the eye. Brain regions were computationally segmented and quantitated, with increased brain volumes with developmental time in uninfected mice. Conversely, in ZIKV-infected mice, no quantitative differences were seen at 3 or 6 dpi, when there are no clinical signs, but qualitatively, diverse visual defects were identified at 6-10 dpi. By 10 dpi, ZIKV-infected mice had significantly lower body weight and reduced volume of brain regions compared to 10 dpi-uninfected or 6dpi ZIKV-infected mice. Nissl and immunofluorescent Iba1 staining on post-diceCT tissue were successful, but RNA extraction was not. Thus, diceCT shows utility for detecting both 3D qualitative and quantitative changes in the developing brain of ZIKV-infected mice, with the benefit, post-diceCT, of retaining the ability to apply traditional histology and immunofluorescent analysis to tissue.

Rabies remains a significant global threat, yet accurate estimations of its impact are hindered by the lack of confirmatory diagnoses. Postmortem confirmation of rabies traditionally involves invasive brain tissue testing, a process met with resistance from deceased patients' families, impeding consent. This paper presents and evaluates an innovative yet unpublished transnasal approach for postmortem brain tissue collection, offering a minimally invasive, easier, faster, and safer method. This method preserves the cadaver's integrity, potentially easing family reluctance towards autopsies. The limited testing of both human and animal rabies in Ghana highlights the challenges in diagnosing this fatal disease. Scarce diagnostic resources and the complexity of obtaining brain tissue samples exacerbate the issue. Cultural and religious beliefs surrounding autopsies contribute to familial hesitation, viewing these procedures as disruptive and disfiguring, further complicating consent. The transnasal technique involves approaching the brain tissue through the nostrils and cribriform plate without any superficial manipulation of the patient's head and face, thereby preserving aesthetics and natural features of the person. Technological advancements and seamless One Health collaboration among governmental, non-governmental, and research entities locally and globally culminated in Ghana's first confirmed rabies diagnosis using this method of brain tissue collection. This success emphasizes the efficiency and feasibility of transnasal brain collection approach and the invaluable role of the One Health approach and collaborative efforts in overcoming diagnostic challenges in rabies control.

Intracranial metastases from thyroid cancer are rare. Although the prognosis of thyroid cancer patients is generally favorable, the prognosis of patients with intracranial metastases from thyroid cancer has been considered unfavorable having a lower survival rate than those without intracranial involvement. Many questions about their management remain unclear. The aim of this study was to analyze the characteristics, treatments, and outcomes of patients with brain metastases from thyroid cancer. Among 4320 patients with thyroid cancer recorded in our institutional database over a 30-year period, 20 patients with brain metastasis were retrospectively collected and analyzed. The clinical characteristics, histological type of primary cancer and metastatic brain tumor, additional previous distant metastasis, treatment modalities, locations and characteristics on radiologic findings, time interval between the first diagnosis of the primary thyroid cancer and brain metastasis, and survival were analyzed. The mean age at initial diagnosis was 59.3 ± 14.1 years, and at the manifestation of diagnosis of cerebral metastasis 64.8 ± 14.9 years. The histological types of the primary thyroid cancers were papillary in ten patients, follicular in seven, and poorly differentiated carcinoma in three. The average interval between the diagnosis of thyroid cancer and brain metastasis was 63.4 ± 58.4 months (range, 0-180 months). Ten patients had a single intracranial lesion and 10 patients had multiple lesions. Surgical resection was primarily performed in 15 patients and whole-brain radiotherapy, radiotherapy or tyrosine kinase inhibitors were applied in the other 5 patients. Overall median survival time was 15 months after diagnosis of BM from TC (range: 1-252 months). Patients with thyroid cancer can develop brain metastasis even many years after diagnosis of the primary tumor. Our study demonstrates an increased overall survival of patients younger than 60 years of age at the time of diagnosis of brain metastasis. There was no difference in survival between patients with brain metastasis from papillary or follicular thyroid carcinoma.

Parkinson's disease (PD) is recognized as the second most prevalent primary chronic neurodegenerative disorder of the central nervous system. Clinically, PD is characterized as a movement disorder, exhibiting an incidence and mortality rate that is increasing faster than any other neurological condition. In recent years, there has been a growing interest concerning the role of the gut microbiome in the etiology and pathophysiology of PD. The establishment of a brain-gut microbiome axis is now real, with evidence denoting a bidirectional communication between the brain and the gut microbiota through metabolic, immune, neuronal, and endocrine mechanisms and pathways. Among these, the vagus nerve represents the most direct form of communication between the brain and the gut. Given the potential interactions between bacteria and drugs, it has been observed that the therapies for PD can have an impact on the composition of the microbiome. Therefore, in the scope of the present review, we will discuss the current understanding of gut microbiome on PD and whether this may be a new paradigm for treating this devastating disease.

Intra Voxel Incoherent Motion (IVIM) imaging provides non-invasive perfusion measurements, eliminating the need for contrast agents. The aim of this work was to explore the feasibility of IVIM in whole brain perfusion studies, where isotropic 1mm voxel is widely accepted as a standard. This study treats on validity of time limited, precise, segmentation ready Whole Brain IVIM imaging protocol suitable for clinical reality. To assess the influence of SNR on the estimation of S0, f, D* and D IVIM parameters a series of measurements and simulations under MATLAB environment were performed for three estimation techniques, utilizing known “ground truth” and noised data. Scanner specific SNR was estimated based on healthy subject IVIM MRI study in 3T scanner. Measurements were conducted for 25,6x25,6x14,4 cm FOV with 256x256 in plane resolution and 72 slices resulting in 1x1x2 mm voxel size. Simulations were performed for 36 SNR levels around measured SNR value. Single voxel grid search estimation method mean relative error for S0 f D* D estimates at measured SNR level were: 5.00%,81.91%, 76.31%, 18.34% respectively. Analysis has shown that high resolution IVIM is possible, although there is significant variation in estimation accuracy and precision depending on SNR level and chosen estimation method.

Technological advances in DBS hardware and software represent a significant growth area in functional neurosurgery. These advancements have the potential to significantly enhance treatment outcomes and expand the scope of neurological disorders that can be effectively addressed through DBS interventions. The introduction of directional DBS marks a new phase in neuromodulation, offering extended benefits for patients with Parkinson's disease, more efficient optimization of clinical outcomes, and targeted treatment of refractory symptoms through data-driven approaches. Implementing a multimodal programming strategy, incorporating novel current fractionation technology and image-guided tools for lead localization and brain sensing, further reduces reliance on traditional trial-and-error programming methods, paving the way for a more predictive application of this therapy. These advancements are expected to drive the development of sophisticated closed-loop stimulation systems capable of integrating continuous data streams for improved patient care.

We construct hypergraphs to analyze functional brain connectivity, leveraging event-related coherence in magnetoencephalography (MEG) data during the visual perception of a flickering image. Principal network characteristics are computed for delta, theta, alpha, beta, and gamma frequency ranges. Employing a coherence measure, a statistical estimate of correlation between signal pairs across frequencies, we generate edge time series, depicting how an edge evolves over time. This forms the basis for constructing an edge-to-edge functional connectivity network. Emphasizing hyperedges as connected components in an absolute-valued functional connectivity network, we focus on exploring these hyperedges in the context of individual variability. Our coherence-based hypergraph construction specifically addresses functional connectivity among four brain lobes: frontal, parietal, temporal, and occipital. This approach enables a nuanced exploration of individual differences within diverse frequency bands, providing insights into the dynamical nature of brain connectivity during visual perception tasks. The results furnish compelling evidence supporting the hypothesis of cortico-cortical interactions occurring across varying scales. The derived hypergraph illustrates robust activation patterns in specific brain regions, indicative of their engagement across diverse cognitive contexts and different frequency bands. Our findings suggest potential integration or multifunctionality within the examined lobes, contributing valuable perspectives to our understanding of brain dynamics during visual perception.

Human longevity is an important but difficult goal due to the extreme complication of human body. If people could repeatedly transfer their consciousness from old bodies to new ones, their lifespan might be prolonged extremely. However, there are several difficulties which prevent the achievement of such a technique. In this paper, we propose an approach that can transfer human consciousness indirectly, and avoid or significantly relieve those difficulties. The strategy of our approach is to integrate the consciousnesses of two bodies (old and new) into a unique consciousness. By doing so, the consciousness is extended to the new body. After that, the consciousness shrinks and remains in the new body when the old body dies. This may also apply to integrating more than two bodies of human, or animal, or even across different species. After investigating thousands of literatures, we find quite strong evidence (related discoveries and technologies) that can support the proposed approach and its advantages. Beside prolonging human lifespan, the approach could also have other meaningful applications.

Attention Deficit Hyperactivity Disorder (ADHD) it is known as a neuropsychiatric disorder. Anatomicaly components with implications in this previously mentioned disorder, are the anterior cingulate gyrus and dorsolateral prefrontal cortex (DLFPC) that are are found having a role in appearing this disease. ADHD is associated with cognitive and functional deficits that relate to diffuse abnormalities in the brain. ADHD is a specific pathology in children but may persisit to youth and also not so hard to find to adults.Till now, hard to find the curative treatment knowing ADHD as a neuropsychiatric disorder with enlarge unknown scientific points. Genetic and environmental component play an important role in diagnosis. Patients life style, a relevant history of individual geneticsand environmental factors are important in diagnosisThe management of ADHD, is also an important part togeter with future trends.

A human brain can communicate with another one’s brain using quantum entanglement. Similar particles can entangle without interaction. Sensory communication between two individuals from far distances is still not known. Former studies primarily have been performed regarding brain neurons' quantum behavior. The test was performed on two individuals far from each other. These individuals were put under the same music on the basis of brain neuroplasticity property. By activating the brain reward system, aligned thinking was time scheduled in these individuals’ brains. On the basis of entanglement, compressed information was sent and received between these two individuals.

Glioblastoma (GBM) is the most common and aggressive adult brain cancer with an average survival rate of around 15 months in patients receiving standard treatment. Oncolytic adenovirus expressing therapeutic transgenes represent a promising alternative treatment for GBM. Of the many human adenoviral serotypes described to date, adenovirus 5 (Ad5) has been most utilized clinically and experimentally. However, the use of Ad5 as an anti-cancer agent may be hampered by naturally high seroprevalence rates to Ad5 coupled with infection of healthy cells via native receptors. To explore whether alternative natural adenoviral tropisms are better suited to GBM therapeutics, we pseudotyped an Ad5 based platform with the fiber knob protein from alternative serotypes. We demonstrate that the adenoviral entry receptors coxsackie and adenovirus receptor (CAR) and CD46 are highly expressed by both GBM and healthy brain tissue, whereas Desmoglein 2 (DSG2) is expressed at low level in GBM. We demonstrate that adenoviral pseudotypes, engaging CAR, CD46 and DSG2, effectively transduce GBM cells. However, the presence of these receptors on non-transformed cells presents the possibility of off-target effects and therapeutic transgene expression in healthy cells. To enhance specificity of transgene expression to GBM, we assessed the potential for tumour specific promoters hTERT and survivin to drive reporter gene expression selectively in GBM cell lines. We demonstrate tightly GBM specific transgene expression using these constructs, indicating that the combination of pseudotyping and tumour specific promoters approaches may enable the development of efficacious therapies better suited to GBM.

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.

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.

The evolution of the vertebrate central nervous system (CNS) represents one of the most remarkable examples of biological complexity emergence. This review traces the developmental trajectory of the CNS from early chordates to modern humans, highlighting key evolutionary innovations. The primitive nerve cord of early chordates evolved into increasingly specialized structures, with major transitions including the development of the tripartite brain, the emergence of the telencephalon, and the progressive elaboration of the cerebral cortex. Critical evolutionary adaptations included the development of neural crest cells, the regionalization of brain structures, and the remarkable expansion of associative areas. The mammalian radiation brought significant advances in brain organization, particularly in the neocortex. The primate lineage witnessed further elaboration of cortical areas, culminating in the human brain's unique features: expanded prefrontal cortex, enhanced connectivity, and sophisticated neural networks supporting advanced cognitive capabilities. This evolutionary journey illuminates how incremental changes in neural organization laid the foundation for human consciousness and cognitive complexity. Keywords: Cephalization • Neurulation • Brain regionalization • Encephalization • Cortical development • Bilateral symmetry • Neuroplasticity • Cognitive evolution • Social brain • Human consciousness

The gut-brain axis (GBA) represents a complex, bidirectional communication network that intri-cately connects the gastrointestinal tract with the central nervous system (CNS). Understanding and intervening in this axis opens a pathway for therapeutic advancements. In light of this, the current review assesses the effectiveness of neuromodulation techniques in treating neurological and gastrointestinal disorders by modulating the GBA, involving key elements such as gut micro-biota, neurotrophic factors, and proinflammatory cytokines. Through a comprehensive literature review encompassing PubMed, Google Scholar, Web of Science, and the Cochrane Library, and analyzing 182 relevant articles, this research highlights how neuromodulation can positively impact the management of functional gastrointestinal disorders (FGIDs), chronic pain, inflammation, and a range of GI disorders like Crohn's disease and ulcerative colitis. Despite existing challenges, the ability of neuromodulation to adjust disrupted neural pathways, alleviate pain, and mitigate in-flammation is significant in improving the quality of life for patients, thereby offering exciting prospects for future advancements in patient care.

Background: The circadian system, a vital temporal regulator influencing physiological processes, has implications for cancer development and treatment response. Our study assesses circadian timing's impact on whole-brain radiotherapy outcomes in brain metastases for personalized cancer therapy insights. Aim: Evaluate circadian influence on radiation treatment timing and its correlation with clinical outcomes. Identify patient populations benefiting from interventions synchronizing circadian rhythms, considering subgroup differences and potential disparities related to social determinants of health (SDoH). Design: IRB-approved retrospective analysis of 237 patients undergoing whole-brain radiotherapy for brain metastases (2017–2021), receiving over 80% of treatments in the morning or afternoon. Survival analyses utilized Kaplan–Meier curves. Setting/Participants: Single-institution study involving patients receiving whole-brain radiotherapy. Collected demographic, disease, and socioeconomic parameters from electronic medical records. Results: Morning treatment (n=158) showed a trend towards improved overall survival vs. afternoon (n=79), median survival 158 vs. 79 days (p=0.20, HR=0.84, CI95% 0.84–0.91). Subgroup benefits for morning treatment in females (p=0.04) and trends in controlled primary disease (p=0.11) and breast cancer metastases (p=0.08). SDoH-based disparities observed, with Black and lower-income patients exhibiting diminished circadian influence. Conclusions: Emphasizes chronobiological factors' relevance in brain metastases radiation therapy. Morning treatment correlates with improved survival, particularly in specific subgroups. Identifies potential circadian influence disparities based on SDoH, laying a foundation for personalized cancer therapy and interventions synchronizing circadian rhythms for enhanced treatment efficacy.