Appropriate diagnosis, treatment and care contributes to better service engagement, improvements to wellbeing, cost savings, reductions in morbidity and mortality for people with Alcohol Related Brain Damage. In the North-East of England large amounts of alcohol are consumed, reflected in the number of alcohol-related deaths in the region. However, the pathway for people with Alcohol Related Brain Damage to receipt of diagnosis, treatment and care is unknown and could be unwittingly influenced by stigma. Qualitative in-depth semi-structured interviews were completed with 25 health and social care professionals from organisations involved with people with Alcohol Related Brain Damage recruited via snowball-sampling. Interviews were recorded, transcribed verbatim, coded, and analysed. People with Alcohol Related Brain Damage were stigmatised both by society and professionals which inhibited entry into services therefore Alcohol Related Brain Damage remained underdiagnosed and misdiagnosed. There was no dedicated service but silos with revolving doors and underfunded generic care with long waiting lists typically excluding those with alcohol or neurological problems. Professionals need to be challenged on the assumption that Alcohol Related Brain Damage is self-inflicted via training aimed at challenging unconscious bias. Reducing stigmatising processes associated with Alcohol Related Brain Damage could counteract professionals’ reluctance to provide care.

(1) Background: Environmental and public health research has given considerable attention to the impact of air quality on brain health, with systematic reviews widespread. No literature review has been done for cognitive frailty – a multidimensional syndrome combining physical frailty and cognitive impairment and their apparent co-dependence, linked to increased vulnerability and adverse health outcomes, including dementia. Instead, cognitive decline and frailty is implicitly explored through research on air quality and comorbid cognitive and physical decline in elderly populations. (2) Methods: A scoping review was conducted to explore the need for a systematic review. Combining Arksey and O’Malley [1] and PRISMA-ScR checklist [2], a scoping review of SCOPUS using ‘cogniti*’ + ‘resilience’ + ‘air quality’ or ‘cogniti*’ + ‘ageing’ + ‘air quality’ resulted in N=2503 articles, screened and reduced using inclusion and exclusion criteria, to N=16 articles. (3) Results: Air quality appears to be a critical risk factor for cognitive decline, even at air quality levels below WHO targets. Moderate long-term ambient air pollution appears linked to increased risk of cognitive frailty, suggesting earlier and more active interventions to protect older people. There are varied effects on cognition across the life course, with both emotional and functional impacts. Effects may be more detrimental to elderly people with existing conditions, including economic and health inequalities. Generalisation of results is limited due to the absence of a dose-response, variations in methods, controlling for comorbid effects, and variance across studies. (4) Conclusions: The findings support the need for more research and a more extensive summary of the literature.

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.

The blood–brain barrier (BBB) plays pivotal roles in synaptic and neuronal functioning by sealing the space between adjacent microvascular endothelial cells. BBB breakdown is present in patients with mild cognitive impairment (MCI) or Alzheimer disease (AD). Claudin-5 (CLDN-5) is a tetra-spanning protein essential for sealing the intercellular space between adjacent endothelial cells in the BBB. In this study, we developed a blood-based assay for CLDN-5 and investigated its diagnostic utility by using 100 cognitively normal (control) subjects, 100 patients with MCI, and 100 patients with AD. Plasma CLDN-5 levels were increased in patients with AD (3.08 ng/mL) compared with controls (2.77 ng/mL). Plasma levels of phosphorylated tau (pTau181), a biomarker of pathological tau, were elevated in patients with MCI or AD (2.86 and 4.20 pg/mL, respectively) compared with control subjects (1.81 pg/mL). In patients with MCI or AD, plasma levels of CLDN-5—but not pTau181—decreased with age, suggesting some age-dependent BBB changes in MCI and AD. These findings suggest that plasma CLDN-5 may a potential biochemical marker for the diagnosis of MCI and AD.

In this observational study, we compared continuous physiological signals during an active stand test in adults aged 50 years and over, characterized as frail by three different criteria, using data from The Irish Longitudinal Study on Ageing (TILDA). Four independent groups were identified: those characterized as frail only by one of the frailty tools used (the physical Frailty Phenotype (FP), the 32-item Frailty Index (FI), or the Clinical Frailty Scale (CFS) classification tree), and a fourth group where participants were not characterized as frail by any of these tools. Continuous non-invasive physiological signals were collected during an active stand test: systolic (sBP) and diastolic (dBP) blood pressure, as well as heart rate (HR), using digital artery photoplethysmography. Additionally, frontal lobe cerebral oxygenation (Oxy), deoxygenation (Deoxy), and tissue saturation index (TSI) were also non-invasively measured using near-infrared spectroscopy (NIRS). The signals were visualized across frailty groups and statistically compared using one-dimensional statistical parametric mapping (SPM). A total of 1,124 participants (mean age 63.5 years, 50.2% women) were included: 23 were characterized as frail only by FP, 97 by FI, 38 by CFS, and 966 by none of these criteria. SPM analyses revealed that only the group characterized as frail by FI had significantly different signals (p<0.05) compared to the non-frail group. Specifically, they exhibited a lesser increase in HR between 5-15 seconds post-stand and larger deficits in sBP and dBP between 15-40 seconds post-stand, and possibly a lower Delta TSI at 20 seconds post-stand. In this comparison, the FI proved more adept at capturing distinct physiological responses to standing, likely due to its direct inclusion of cardiovascular morbidities in its definition.

Multiple sclerosis is a chronic, autoimmune disease that mainly affects the central nervous system, including the brain, spinal cord, and optic nerve. This disease can cause clinical symptoms such as cognitive decline, muscle weakness, spasms, and fatigue in patients, and the onset tends to be younger. Current medication can only prevent or alleviate symptoms, so early diagnosis of this disease can increase patients' chances of treatment. Although the use of nuclear magnetic resonance detection can improve the efficiency of early auxiliary diagnosis, it still requires experienced doctors to spend too much time and energy on comprehensive judgment. To reduce the time cost and improve the efficiency of multiple sclerosis diagnosis, this article proposes a detection and recognition algorithm for multiple sclerosis based on wavelet entropy and self-adaptive particle swarm optimization. Firstly, a triple discrete wavelet transform is performed on the brain image of multiple sclerosis, and then 10 wavelet entropies are extracted from the decomposed wavelet subbands, which can reduce the feature dimensions of the image; Then, the algorithm of self-adaptive particle swarm optimization is used to optimize the feedforward neural network, in order to obtain the optimal connection weights and thresholds during the training process. The result of the model is with an average sensitivity of 92.29±1.89, specificity of 92.54±0.67, precision of 92.48±0.59, accuracy of 92.42±0.88, and F1 score of 84.85±1.74, Matthews correlation coefficient of 92.37±0.96, and Fowlkes223 Mallows Index of 92.38±0.96. The experimental results indicate that this algorithm has a very important data support role in detecting multiple sclerosis.

Objective: To investigate whether impaired plantar cutaneous vibration perception contributes to axial motor symptoms in Parkinson’s disease (PD) and whether anti-parkinsonian medication and subthalamic nucleus deep brain stimulation (STN-DBS), show different effects. Methods: Three groups were tested: PD patients on medication (PD-MED), PD patients on medication and additional STN-DBS (PD-MED–DBS), and healthy subjects (HS) as reference. Motor performance was analyzed using a pressure distribution platform. Plantar cutaneous vibration perception thresholds (VPT) were investigated using a customized vibration exciter at 30 Hz. Results: Motor performance of PD-MED and PD-MED–DBS was characterized by greater postural sway, smaller limits of stability ranges, and slower gait, due to shorter strides, fewer steps per minute, and broader stride widths compared to HS. Comparing patient groups, PD-MED–DBS showed better overall motor performance than PD-MED, particularly for the functional limits of stability and gait. VPTs were significantly higher for PD-MED compared to HS, which suggests impaired plantar cutaneous vibration perception in PD. However, PD-MED–DBS showed less impaired cutaneous vibration perception than PD-MED. Conclusion: PD patients suffer from poor motor performance compared to healthy subjects. Anti-parkinsonian medication in conjunction with STN-DBS seems to be superior for normalizing axial motor symptoms compared to medication alone. Plantar cutaneous vibration perception is impaired in PD patients, whereas anti-parkinsonian medication together with STN-DBS is superior for normalizing tactile cutaneous perception compared to medication alone. Consequently, based on our results and the findings of the literature impaired plantar cutaneous vibration perception might contribute to axial motor symptoms in PD.

Non-suicidal self-injurious behavior (NSSI), prevalent in patients with non-psychotic mental disorders (NPMD), is associated with numerous adverse outcomes. Despite active research into the clinical and psychological aspects of NSSI, the underlying biological mechanisms remain obscure. Early adverse experiences are believed to induce long-lasting changes in neuroendocrine mechanisms of stress control playing a key role in NSSI development. The aim of the study was to evaluate parameters potentially predicting development of NSSI in female patients with NPMD. Eighty female patients over 18 years with NPMD and suicidal ideation (40 with and 40 without NSSI) and 48 age matching women without evidence of mental illness (healthy controls) were enrolled. Diagnostic interviews and self-report measures were used to assess childhood maltreatment, presence, frequency, and characteristics of suicidal and self-injurious thoughts and behaviors, the Beck Depression Inventory scale to assess severity of depression. Hypothalamic-pituitary-adrenal axis markers, hormones, and neurotrophic factors were measured in blood serum. The likelihood of developing NSSI in patients with NPMD was associated with early adverse family history and elevated adrenocorticotropic hormone levels. Dysregulation of hypothalamic-pituitary-adrenal axis as a result of early chronic stress experiences may represent critical biological mechanism promoting the development of NSSI behaviors in patients with NPMD.

CLIPPERS which stand for Chronic lymphocytic inflammation with pontine perivascular enhancement responsive to steroids, is a chronic inflammatory disorder of the central nervous system. The aetiology of CLIPPERS remains unclear, although its pathogenesis shows immune-mediated processes. The diagnosis of CLIPPERS is challenging without a specific biomarker hence, it is important to consider if both the clinical and radiological features are consistent with the diagnosis, or rather any other disease that mimics CLIPPERS. The Authors present a case of a 40-year-old Female patient diagnosed with CLIPPERS syndrome in India. Differential diagnosis, clinical and MRI characteristics of CLIPPERS syndrome, and treatment approaches are discussed.

The circadian clock is a 24-hour cycle within the body that regulates various factors, including sleep, body temperature, and hormone secretion. It allows the body to adjust to the light and dark cycle. Disruptions to the circadian rhythm are important risk factors for many diseases, including neurodegenerative illnesses. The central clock is controlled by the clock genes in the suprachiasmatic nucleus (SCN) of the brain, and one of the main functions of the circadian clock is to regulate lipid metabolism. There has been a lack of investigation on the circadian regulation of lipid metabolism-related apolipoprotein genes in the brain; thus, this study sought to summarize the rhythmic expression of clock genes and lipid metabolism-related apolipoprotein genes within the SCN of Mus musculus. Out of the 20 apolipoprotein genes that were studied by the published database, all 9 genes were highly expressed in the SCN. Most of the 6 genes showed rhythmic expression in the brain of mice, suggesting that the master clock might regulate them. The results, therefore, reveal a potential target for preventing and treating circadian disorders. We summarized most studies of lipid-related apolipoprotein genes within limited locations of the SCN and brain to further understand how disordered cerebral lipid metabolism causes multiple brain diseases and disorders. We reviewed recent studies, determined the unexplored questions, and identified a potential direction for further research.

Central Nervous System (CNS) cancers pose a formidable challenge in the medical world, characterized by aggressive behaviors and limited therapeutic options. The emergence of nanomedicine has offered new hope in CNS cancer treatment. The COVID-19 pandemic has further accelerated the need for innovative therapeutic strategies, emphasizing the significance of nanomedicine in this era. This mini review explores the current status of nanomedicine in CNS cancer therapy, with a particular focus on the post-COVID-19 landscape. We discuss the unique challenges presented by CNS cancers, the potential of nanomedicine in overcoming these challenges, and the recent developments in the field. Additionally, we highlight the lessons learned from the pandemic and how they can be applied to improve CNS cancer therapeutics. We also shed light on the evolving regulatory landscape and the prospects of personalized nanomedicine in CNS cancer treatment. The integration of nanomedicine in CNS cancer therapy is becoming increasingly promising, and its role in the post-COVID-19 era is poised to shape the future of neuro-oncology.

This paper first introduces the main classification of brain diseases and the main causes of these diseases. It is followed by wavelet analysis, which is a mathematical function or wave-like pattern used to transform data, which can decompose the signal into different wavelet functions, each of which is related to a specific scale or frequency. Wavelet analysis has been applied in many fields such as image processing, data analysis and engineering. In addition, wavelet is also used in the analysis of biological signals. Wavelet analysis breaks down brain signals, such as EEG or fMRI data, into various frequency components at different scales. Wavelet analysis provides time-frequency localization. Pattern recognition can be enhanced by isolating salient features in the data. Wavelet denoising can effectively separate noise from underlying brain signals. Wavelet denoising usually adopts threshold method. Wavelet analysis can enhance pattern recognition by isolating salient features in the data. Researchers can train machine learning models based on these wavelet-derived features to recognize specific patterns associated with different neurological disorders. Wavelet analysis can track these changes by continuously evaluating the frequency content of the neuroimage data over time. Through continuous efforts, wavelet theory and technology have become valuable tools in the field of neuroscience and brain disease research.

This review summarizes the currently known biochemical neuroadaptive mechanisms of remote ischemic conditioning. In particular, it focuses on the significance of the pro-adaptive effects of remote ischemic conditioning, which allow prevention of neurological and cognitive impairments associated with hippocampal dysregulation after brain damage. The neuro-immuno-humoral pathway of transmitting a conditioning stimulus, as well as the molecular basis of the early and delayed phases of neuroprotection, including anti-apoptotic, antioxidant and anti-inflammatory components, are also outlined. Based on the close interplay between the effects of ischemia, especially mediated by interaction of HIF factors and steroid hormones, the involvement of the hypothalamic-pituitary-adrenocortical system in remote ischemic conditioning is also discussed.

Intracranial compliance (ICC) plays a pivotal role in understanding the underlying mechanisms of various brain disorders and is of great clinical importance. Therefore, addressing the challenges in practical application of ICC is crucial for neurosurgeons. This study explored the significance of ICC assessment considering the time-dependency of specific brain disorders through two distinct approaches: short and large time elapsed (TE) in measuring volume or intracranial pressure (ICP) changes in the ICC equation (∆Volume/∆ICP). Variations in ICC values were observed across various ICC assessment methods and different TE values. Notably, the compensatory response of the brain exhibited non-monotonic and variable changes in a large TE for certain brain disorders, diverging from patterns observed in short TE assessments. Furthermore, the recovery behavior of the brain changed under different brain disorders when exposed to short and long TE conditions. These findings emphasized the dynamic nature of ICC and provided valuable insights into the correct practical assessment of ICC by selecting the appropriate TE, as well as considering the differences in strain rates and loading durations on the brain in different brain disorders. These insights also shed light on the reasons why, despite its clinical significance, ICC monitoring has not yet become a standard component of clinical care, unlike ICP monitoring.

Traumatic brain injury (TBI) is among the leading causes of mortality and long-term impairment globally. TBI has a dynamic pathology encompassing a variety of metabolic and molecular events that occur in two phases, primary and secondary. An external forceful blow to the brain initiates the primary phase, which is followed by a secondary phase that involves the release of calcium ions (Ca2+) and the initiation of a cascade of inflammatory processes, including mitochondrial dysfunction, rise in oxidative stress, activation of glial cells, and damage to the blood-brain barrier (BBB), resulting in paracellular leakage. There is currently no FDA-approved drug for TBI, but existing approaches rely on delivering small and macromolecular treatments, which are severely constrained by the BBB, poor retention, off-target toxicity, and complex pathology of TBI. Therefore, there is a demand for innovative and alternative therapeutics with effective delivery tactics for diagnosis and treatment of TBI. Tissue engineering and use of biomaterials is one such alternative approach. With this approach, neuronal stem cell therapy is combined with synthetically generated tissue materials such as hydrogels, self-assembling peptides, and electrospun nanofibers, which may induce neurite outgrowth, differentiation of human neural stem cells, and nerve gap bridging in TBI. This review examines tissue engineering and the use of biomaterials as potential treatments for TBI, including their synthesis, mechanisms of action, and limitations. The review also discusses challenges facing tissue engineering and biomaterial technology including survival rate of transplanted stem cells and the development of biodegradable, biocompatible, and mechanically flexible biomaterials. A better understanding of the mechanisms and drawbacks of these novel therapeutic approaches will help guide the design of future TBI therapies.

Chronic traumatic encephalopathy (CTE) is a unique neurodegenerative disease that is associated with repetitive head impacts (RHI) in both civilian and military settings. In 2014, the research criteria for the clinical manifestation of CTE, traumatic encephalopathy syndrome (TES) were proposed to improve the clinical identification and understanding of the complex neuropathological phenomena underlying CTE. This review provides a comprehensive overview of the current understanding of the neuropathological and clinical features of CTE, proposed biomarkers of traumatic brain injury (TBI) in both research and clinical settings, and a range of treatments based on previous preclinical and clinical research studies. Due to the heterogeneity of TBI, there is no universally agreed-upon serum, CSF, or neuroimaging marker for its diagnosis. However, as our understanding of this complex disease continues to evolve, it is likely that there will be more robust, early diagnostic methods and effective clinical treatments. This is especially important given the increasing evidence of a correlation between TBI and neurodegenerative conditions, such as Alzheimer's disease and CTE¹. As public awareness of these conditions grows, it is imperative to prioritize both basic and clinical research, as well as the implementation of necessary safe and preventative measures.

Our previous studies showed that in patients with brain diseases neurotrophic factors in lacrimal fluid (LF) may change more prominently than in blood serum (BS). Since glial cell line-derived neurotrophic factor (GDNF) is involved in control of neuronal networks in epileptic brain, we aimed to assess GDNF levels in LF and BS as well as BDNF, hypothalamic-pituitary-adrenocortical and inflammation indices in BS of patients with focal epilepsy (PWFE), epilepsy and comorbid depression (PWFE+MDD) compared with major depressive disorder (PWMDD) and healthy controls (HC). GDNF levels in BS were similar in patients and HC and higher in PWFE taking valproates. GDNF levels in LF were significantly lower in all patient groups compared to controls, and independent of drugs used. LF and BS GDNF concentrations positively correlated in HC, but not patient groups. BDNF level was lower in BS of patients compared with HC and higher in PWFE+MDD taking valproates. Logistic regression models demonstrated that GDNF decrease in LF may be an important predictor of focal epilepsy. Probability of focal epilepsy can be evaluated using GDNF in LF and BDNF in BS; MDD - GDNF in LF, cortisol and TNF-α in BS; epilepsy with MDD - GDNF in LF, TNF-α and BDNF in BS.

Research conducted on individuals with depression reveals that major depressive disorders (MDDs) coincide with diminished levels of the inhibitory neurotransmitter γ-aminobutyric acid (GABA) in the brain, as well as modifications in the subunit composition of the primary receptors (GABAA receptors) responsible for mediating GABAergic inhibition. Furthermore, there is substantial evidence supporting the significant role of GABA in regulating stress within the brain, which is a pivotal vulnerability factor in mood disorders. Although there is substantial evidence indicating that GABA may be affecting GABA receptors in peripheral tissues, there is comparatively less evidence supporting its direct action within the brain. Emerging evidence highlights that GABA may exert beneficial effects on the brain and psyche through the gut-brain axis. GABA is readily available and approved as a food supplement in many countries. While GABA enjoys wide consumer acceptance in Eastern Asian markets, with many consumers reporting favorable effects on stress regulation, mood, and sleep, rigorous independent research is still largely lacking. Basic research, coupled with initial clinical findings, makes GABA an intriguing neuro-nutritional compound deserving of clinical studies in individuals with depression and other psychological problems.

Familial Exudative Vitreoretinopathy (FEVR), Norrie disease, and persistent fetal vascular syndrome (PFVS) are extremely rare retinopathies that are clinically distinct but are unified by abnormal retinal endothelial cell function – and subsequent irregular retinal vascular development and/or aberrant inner blood-retinal-barrier (iBRB) function. The early angiogenesis of the retina and its iBRB is a delicate process that is mediated by the canonical Norrin Wnt-signaling pathway in retinal endothelial cells. Pathogenic variants in genes that play key roles within this pathway such as NDP, FZD4, TSPAN12, and LRP5, have been associated with the incidence of these retinal diseases. Recent efforts to further elucidate the etiology of these conditions have not only highlighted their multigenic nature but have also resulted in the discovery of pathological variants in additional genes such as CTNNB1, KIF11, and ZNF408, some of which operate outside of the Norrin Wnt-signaling pathway. Recent discoveries of FEVR-linked variants in two other Catenin genes (CTNND1, CTNNA1) and the Endoplasmic Reticulum Membrane Complex Subunit-1 gene (EMC1) suggest that we will continue to find additional genes that impact the neural retinal vasculature, especially in multi-syndromic conditions. The goals of this review are to briefly highlight the current understanding of the roles of their encoded proteins in retinal endothelial cells to understand the essential functional mechanisms that can be altered to cause these very rare pediatric retinal vascular diseases.

Brain arteriovenous malformations (BAVMs) are a critical concern in hereditary hemorrhagic telangiectasia (HHT) patients, carrying the risk of life-threatening intracranial hemorrhage. While traditionally seen as congenital, the debate continues due to documented de novo cases. Our primary goal was to identify the precise postnatal window in which deletion of the HHT gene Endoglin (Eng) triggers BAVM development. We employed SclCreER(+);Eng2f/2f mice, enabling timed Eng gene deletion in endothelial cells via tamoxifen. Tamoxifen was given at four postnatal periods: P1-3, P8-10, P15-17, and P22-24. BAVM development was assessed at 2-3 months using latex dye perfusion. We examined angiogenic activity by assessing vascular endothelial growth factor receptor 2 (VEGFR2) expression via Western blotting and Flk1-LacZ reporter mice. Longitudinal magnetic resonance angiography (MRA) was conducted up to 9 months. BAVMs emerged in 88% (P1-3), 86% (P8-10), and 55% (P15-17) of cases, with varying localization. Notably, the P22-24 group did not develop BAVMs but exhibited skin AVMs. VEGFR2 expression peaked in the initial 2 postnatal weeks, coinciding with BAVM onset. These findings support the “second hit” theory, highlighting the role of early postnatal angiogenesis, in initiating BAVM development in HHT type I mice.

This article reviews the introduction of Alzheimer's Disease (AD), neural networks, training and learning of neural networks, applications of neural networks in early diagnosis of AD, applications of neural networks in AD drug discovery, other brain diseases, and challenges faced by AD. First, the paper introduces the background and characteristics of AD. AD is a degenerative neurological disorder characterized by impaired memory, decreased cognitive function, and loss of neurons. These characteristics place a huge burden on the lives and families of patients. Next, the basic principle and structure of neural network are discussed. A neural network is a computational model made up of multiple neurons that can perform tasks by learning and adapting to input data. In particular, the key concepts of neural network hierarchy, activation function and weight adjustment are discussed. Then, the training and learning methods of neural networks are discussed. Common techniques such as backpropagation algorithm and gradient descent optimizer are introduced in detail, as well as the importance of data preprocessing and model evaluation. Next, the paper focuses on the application of neural network in early diagnosis of AD. By extracting features from brain image data, neural networks can automatically identify differences between AD patients and healthy subjects, enabling early diagnosis and intervention. In addition, the application of neural networks in AD drug discovery is also discussed. By analyzing and predicting a database of known drugs, neural networks can help discover potential treatments for AD and speed up the drug discovery process. The paper further explores the application of neural networks in other brain diseases and highlights the challenges faced by AD, such as the lack of reliable biomarkers, complex pathological mechanisms, etc. In summary, this paper presents a systematic overview of AD, neural networks, training and learning of neural networks, applications of neural networks in early diagnosis of AD and drug discovery, and other brain diseases and challenges associated with AD.

Background: Aging rate is affected by genetic changes, epigenetic modifications, oxidative stress, inflammation, lifestyle and environmental factors. In accelerated aging (AA), biological age exceeds the chronological one. Objective: To undertake a critical reappraisal of the AA concept and to reveal its weaknesses and limitations. Methods: We reviewed over 300 recent articles dealing with physiology of brain aging and pathophysiology of neurodegeneration. Results: (1) Organ systems age at different rates, which interferes with application of the AA concept to individual organs. (2) Aging rate can be decelerated due to individual structure–functional reserves built with cognitive, physical training or pharmacological interventions. (3) The AA concept lacks standardised terminology and methodology. (4) Specific molecular biomarkers (MBM) reflect aging. To consolidate the AA theory, researchers should validate numerous MBM candidates. (5) Aging factors, mechanisms and the exact nature of their biological outcomes are not well understood. Conclusion: Although considered as a perspective theory, the AA concept has serious limitations and it requires an update.

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.

While it is well known that 98-99% of the human genome do not encode proteins, but are nevertheless transcriptionally active and give rise to a broad spectrum of noncoding RNAs (ncRNAs) with complex regulatory and structural functions, specific functions have so far been assigned to only a tiny fraction of all known transcripts. On the other hand, the striking observation of an overwhelmingly growing fraction of ncRNAs, in contrast to an only modest increase in the number of protein-coding genes, during evolution from simple organisms to humans, strongly suggests critical but so far essentially unexplored roles of the noncoding genome for human health and disease pathogenesis. Research into the vast realm of the noncoding genome during the past decades thus lead to a profoundly enhanced appreciation of the multi-level complexity of the human genome. Here, we address a few of the many huge remaining knowledge gaps and consider some newly emerging questions and concepts of research. We attempt to provide an up-to-date assessment of recent insights obtained by molecular and cell biological methods, and by the application of systems biology approaches. Specifically, we discuss current data regarding two questions: (1) By which mechanisms could evolutionary recent ncRNAs with critical regulatory functions in a broad spectrum of cell types (neural, immune, cardiovascular) constitute novel thera-peutic targets in human diseases ? (2) Since noncoding genome evolution is causally linked to brain evolution, and given the pro-found interactions between brain and immune system, could human-specific brain-expressed ncRNAs play a direct or indirect (immune-mediated) role in human diseases? Synergistic with the remarkable recent progress regarding delivery, efficacy, and safety of nu-cleic acid-based therapies, the ongoing large-scale exploration of the noncoding genome for human-specific therapeutic targets is encouraging to proceed with the development and clinical evaluation of novel therapeutic pathways suggested by these research fields.

Network neuroscience delves into comprehending the intricate arrangement and interactions within the neural networks of the brain. By merging insights from both neuroscience and network theory, it investigates the brain's structure and function through the lens of interconnected nodes (symbolizing brain regions) and edges (symbolizing the connections among these regions) forming a dynamic network. Graph metrics play a pivotal role in neuroscience by providing quantifiable insights into the intricate connectivity patterns within the brain's neural networks. Frequently, nodes are extracted from functional or structural atlases, which can lead to diverse shapes and sizes. Nevertheless, our understanding of how these differing node characteristics and definitions impact the computed graph metrics in neuroimaging data remains limited. This study adopts a data-driven methodology to delineate functional nodes, subsequently examining the influence of their sizes on resultant graph metrics. By employing the Neuromark framework, an entirely automated independent component analysis (ICA) is applied to resting state fMRI data. Through this, functional network connectivity (FNC) matrices are computed—capturing Pearson correlations between component-time courses—while employing a proportional threshold to streamline node connections based on these correlations. Subsequently, various global and local graph metrics are computed, offering insights into network characteristics. Global metrics provide an overarching summary of the network structure, while local measures delve into structural intricacies at the individual component level. Node sizes are computed based on voxel counts surpassing a designated threshold. Next, we calculated the Pearson correlation between the obtained node sizes and the graph metrics, which we term 'node-metric coupling' (NMC). Our findings revealed consistent and noteworthy correlations between the values of graph metrics and the dimensions of brain nodes. To delve deeper into the implications of this correlation, we examined the node-metric coupling within a dataset comprising Alzheimer's disease, mild cognitive impairment, and control subjects. The disparities observed in node-metric coupling among these groups underscore the necessity of accounting for this factor during analysis. The two principal outcomes of this study are as follows: Firstly, the substantial interplay between varying node sizes within a given atlas and the resultant graph metrics; and secondly, the potential utility of node-metric coupling as a viable biomarker for brain disorders. These discoveries hold significant ramifications. While comparing studies employing diverse atlases is already a challenge, our work highlights an additional, critical source of variability: accounting for node sizes. Consequently, the association between intra-atlas node size and graph metric should be thoughtfully acknowledged in future neuroimaging investigations.

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.

Understanding the phenomena underlying the non-selective susceptibility to ischemia of py-ramidal neurons in the CA3 area of the hippocampus is important from the point of view of elu-cidating the mechanisms of memory loss and the development of post-ischemic dementia. We used an ischemic model of Alzheimer's disease to study changes in amyloid protein precursor gene expression, its cleavage enzymes and tau protein in the CA3 area of the hippocampus af-ter a 10-minute brain ischemia with 12, 18, and 24-month survival. Quantitative reverse tran-scriptase PCR assay showed that the expression of all the genes that contribute to amyloid pro-duction was dysregulated within 2 years in the CA3 area of the hippocampus after ischemia. The expression of the amyloid protein precursor gene was above the control values at all times of the study. The expression of the α-secretase gene also exceeded the control values throughout the study. In contrast, the expression of the β-secretase gene reaching its maximum increase 12 months after ischemia, was below control values after 18 months and again above control values after 24 months of survival. Presenilin 1 and 2 gene expression was significantly elevated throughout the follow-up period, with peak expression of both genes occurring 12 months after ischemia. This suggests that the genes studied are involved in the non-amyloidogenic processing of amyloid protein precursor. Also, tau protein gene expression was significantly elevated throughout the observation period, and peak gene expression was present 12 months after is-chemia. Data indicate that an episode of brain ischemia with long-term survival causes damage and death of pyramidal neurons in the CA3 area of the hippocampus in a manner dependent on modified tau protein. Thus defining a new and important mechanism of pyramidal neuronal death in the CA3 area after ischemia. In addition tau protein gene modification after brain is-chemia is useful in identifying ischemic mechanisms occurring in Alzheimer's disease.

Keywords: bariatric surgery, sleeve gastrectomy, Roux-en-y gastric bypass, obesity, microbiota, gut-brain axis, beck scale, depression, diet, probiotics

The MMP-9-1562C/T polymorphism influence incidence and course of many diseases of the central nervous system. We found, using luciferase assays and Q-RT-PCR technique, allele-specific in-fluence of MMP-9-1562C/T polymorphism on the MMP-9 promoter activity and on the expression of MMP-9 mRNA in human neurons derived from SH-SY5Y cells. Then, we have elucidated the mechanism responsible for the allele-specific action of the MMP-9-1562C/T polymorphism on transcriptional regulation of the MMP-9 gene using pull-down assay combined with mass spec-trometry analysis, EMSA and EMSA supershift techniques, as well as DsiRNA-dependent gene silencing. We have found that MMP-9 promoter activity and MMP-9 mRNA expression are reg-ulated in human neurons in the MMP-9-1562C/T allele-specific manner with stronger upregulation conferred by the C allele. Moreover, we have revealed that the allele-specific action of the MMP-9-1562C/T polymorphism on the neuronal MMP-9 expression is related to HDAC1 and ZNF384 transcriptional regulators. We show that HDAC1 and ZNF384 bind differentially to the C and the T alleles forming in vitro different regulatory complexes. Moreover, our data demonstrate that HDAC1 and ZNF384 downregulate differentially the MMP-9 gene promoter activity and MMP-9 mRNA expression in vivo in human neurons acting mostly via the T allele.

Background: Glioblastoma is the most common primary brain neoplasm in adults, with still a poor prognosis despite a constant effort to improve patients’ survival. Some neuroradiological volumetric parameters seem to play a predictive role on Overall Survival (OS) and Progression Free Survival (PFS). The aim of this study is to analyze the impact that the volumetric areas of contrast-enhancing tumor and perineoplastic edema have on survival of patients treated for glioblastoma; Methods: A series of 87 patients who underwent surgery was retrospectively analyzed; OS and PFS were considered as the end points of the study. For each patient a multidisciplinary revision was conducted in collaboration with the Neuroradiology and Neuro-Oncology board. A manual and semi-automatic measurement were adopted to perform the radiological evaluation: contrast Enhancement Preoperative (CE-PTV) and Postoperative Tumor Volume (CE-RTV), Edema/Infiltration Preoperative (T2/FLAIR-PV) and Postoperative Volume (T2/FLAIR-RV); necrosis volume inside the tumor (NV); total tumor volume, including necrosis (TV); Results: The median OS value was 9 months and the median PFS value was 4 m; the mean values were respectively 12,3 m and 6,9 m. Multivariate analysis showed that the OS related factors were: adjuvant chemo-radiotherapy (p &lt; 0,0001), CE-PTV &lt; 15 cm³ (p=0,03), surgical resection &gt; 95% (p=0,004) and the presence of a “pseudo-capsulated” radiological morphology (p=0,04); Conclusions: maximal safe resection is one of the most relevant predictive factors for patients’ survival. The semi-automatic pre-operative MRI evaluation could play a key role in prognostically categorizing these tumors.

Device-mediated, non-invasive drug delivery across the blood-brain barrier (BBB) represents a significant advancement in treating neurological diseases. The BBB is a tightly packed layer of endothelial cells that shields the brain from harmful substances in the blood, allowing necessary nutrients to pass through. It is a highly selective barrier, which poses a challenge to delivering therapeutic agents into the brain. Several non-invasive techniques and devices have been proposed or investigated to enhance drug delivery across the BBB. This paper presents the current state of the art and case studies that address the pharmacology, technology, delivery systems, regulatory approval, ethical concerns, and future possibilities.

Approximately 6 million youth aged 12 to 20 consume alcohol monthly in the United States. The effect of alcohol consumption in adolescence on behavior and cognition is heavily researched, however, little is known about how alcohol consumption in adolescence may alter brain function, leading to long-term developmental detriments. In order to investigate differences in brain connectivity associated with alcohol use in adolescents, brain networks were constructed using resting state functional magnetic resonance imaging data collected by the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) from 698 youth (12-21 years, 117 hazardous drinkers and 581 no/low drinkers). Analyses assessed differences in brain network topology based on alcohol consumption in eight pre-defined brain networks, as well as in whole-brain connectivity. Within the central executive network (CEN), basal ganglia network (BGN), and sensorimotor network (SMN), no/low drinkers demonstrated stronger and more frequent connections between highly globally efficient nodes, with fewer and weaker connections between highly clustered nodes. Inverse results were observed within the dorsal attention network (DAN), visual network (VN), and frontotemporal network (FTN), with no/low drinkers demonstrating weaker connections between nodes with high efficiency and increased frequency of clustered nodes compared to hazardous drinkers. Results from this study show clear organizational differences between adolescents with no/low or hazardous alcohol use, suggesting that aberrant connectivity in these brain networks is associated with risky drinking behaviors.

Here we performed a comparative experimental analysis by EPR spectroscopy of the intensity of nitric oxide (NO) production and copper content in the injured and uninjured areas of the frontal lobes and the hippocampus of the brain of male Wistar rats, after modeling of combined brain and spinal cord injury. Brain and spinal cord injury were modelled by local destruction of the left precentral region of the brain using a stylet followed by hemorrhage injury at the level of the first lumbar vertebra of the spinal cord. We found a significant decrease in NO production 7 days after injury modeling in the injured and uninjured (contralateral) brain regions, but the copper content remained unchanged one week after injury modeling. Thus, combined brain and spinal cord injury is not accompanied by a radical change in the activity of the antioxidant system in the brain, which is also confirmed by the absence of changes in NO production and copper content in the hippocampus.

The term neurodegeneration with brain iron accumulation (NBIA) brings together a broad set of progressive and disabling neurological genetic disorders in which iron is deposited preferentially in certain areas of the brain. Among NBIA disorders, the most frequent subtype is pantothenate kinase-associated neurodegeneration (PKAN) caused by pathologic variants in the PANK2 gene codifying the enzyme pantothenate kinase 2 (PANK2). Nowadays, there are no effective treatments to stop the progression of these diseases. This review discusses the utility of patient-derived cell models as a valuable tool for the identification of commercial pharmacological or natural compounds for implementing polytarget precision medicine in PKAN. In the last years, several studies have described that PKAN patient-derived fibroblasts manifest the main pathological changes associated with the disease including intracellular iron overload. Interestingly, treatment of mutant cell cultures with various supplements such as pantothenate, pantethine, thiamine, L-carnitine, vitamin E, omega 3, and -lipoic acid improved all pathophysiological alterations in PKAN fibroblasts with residual expression of the PANK2 enzyme. The information provided by pharmacological screenings in patient-derived cellular models can help to optimize therapeutic strategies in individual PKAN patients.

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.

Alzheimer’s disease (AD) and vascular dementia (VaD) together contribute to almost 90% of all dementia cases leading to major health challenges of our time with a substantial global socioeconomic burden. While in Alzheimer’s disease, the improved understanding of Amyloid beta (Aß) mismetabolism and tau hyperphosphorylation as pathophysiological hallmarks has led to significant clinical breakthroughs, similar advances in VaD are lacking. We thus highlight here the importance of shared pathomechanisms found in AD and VaD: Endothelial damage, blood brain barrier (BBB) breakdown and hypoperfusion inducing oxidative stress, inflammation and demyelination and thus trophic uncoupling in the neurovascular unit. A dysfunctional endothelium and BBB lead to the accumulation of neurotoxic molecules and Aß through impaired clearance, which in turn leads to neurodegeneration. In this context we discuss possible neuropathological parameters, which might serve as biomarkers and thus improve diagnostic accuracy or reveal targets for novel therapeutic strategies for both forms of dementia.

The microbiota–gut–brain axis has garnered increasing attention in recent years for its role in various health conditions, including neuroinflammatory disorders like complex regional pain syndrome (CRPS). CRPS is a debilitating condition characterized by chronic neuropathic pain, and its etiology and pathophysiology remain elusive. Emerging research suggests that alterations in the gut microbiota composition and function could play a significant role in CRPS development and progression. Our paper explores the implications of microbiota in CRPS and the potential therapeutic role of boron (B). Studies have demonstrated that individuals with CRPS often exhibit dysbiosis, with imbalances in beneficial and pathogenic gut bacteria. Dysbiosis can lead to increased gut permeability and systemic inflammation, contributing to the chronic pain experienced in CRPS. B, an essential trace element, has shown promise in modulating the gut microbiome positively and exerting anti-inflammatory effects. Recent preclinical and clinical studies suggest that B supplementation may alleviate neuropathic pain and improve CRPS symptoms by restoring microbiota balance and reducing inflammation. Our review highlights the complex interplay between microbiota, inflammation, and neuropathic pain in CRPS and underscores the potential of B as a novel therapeutic approach to target the microbiota–gut–brain axis, offering hope for improved management of this challenging condition.

Anterior-tooth (ANT) contacts induce short latency reflex inhibition of human jaw-closing muscles. The jaw is a rigid class 1 lever for pinpoint-targeting muscle force into a single bite-point, the pivoting food particle. See-saw reflex movements around the food particle fulcrum multiply the food-crushing force. Unpredictable jolts of reaction force caused by food-crushing are subjected to the rostral ANT and caudally to the two articulate ends of the jaw triangle. Compression/distraction strains of food-crushing must be monitored and inhibited by withdrawal reflexes. The mesencephalic ganglion (Vmes), neural myelin sheath, and muscle stretch receptors evolved subsequently to the advent of jaws to improve the velocity of proprioceptive and withdrawal reflexes. In mammalians, the spindles of the taut motor units, stretched by the food-fulcrum send excitatory monosynaptic feedback for the efferent neurons of the respective ipsilateral muscle units, via Vmes. In the Vmes, the spindle-input-mediating afferent neurons are coupled with another source of afferent feedback, which is also excitatory, from the back-tooth (BAT) mechanoreceptors. The two sources of excitatory pulses are summated and targeted for the efferent neurons to boost the stretched and taut motor units. Likewise, the afferent feedback from ANT mechanoreceptors is also coupled in the Vmes with concomitant feedback from spindles. The ANT output, however, is inhibitory to negate the excitatory feedback from the stretched jaw-muscle units. The inhibitory feed from ANT temporarily blocks the excitatory potential of masticatory motor efferent neurons to protect the ANT and jaw-joints from inadvertent strains. The inhibitory inputs from ANT alternate with the excitatory inputs from BAT to determine which jaw-closing muscle units are activated or inhibited at any given instant of food-crushing. The Vmes exists in all jawed vertebrates, and its’ evolution was probably motivated by demands for the control of bite force. The monosynaptic unilateral food-crushing excitatory and inhibitory reflexes (UFCR) override the coexisting bilaterally executed feed for jaw muscles from the central nervous system. Hypothesis: The Vmes-mediated UFCR combine neural inputs from tooth contacts with concomitant feedback from muscle stretch receptors for the control of mammalian food-crushing bite force.

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.

Non-pharmacologic options like the ketogenic diet (KD) and intermittent fasting (IF) are practical nutritional interventions with minor reported side effects like gastrointestinal symptoms, dyslipidemia, and hypomagnesemia for various medical ailments. In conjunction with IF, KD shows promise in weight loss, diabetes management, cardiovascular disorders, polycystic ovarian syndrome, cancer, and chronic neurological disorders. Based on prior research, we have examined the mechanism of action of KD and IF and their effect on neurological diseases, cancer, and obesity. We have also suggested evidence-based recommendations for the safer practice of KD and IF. Despite potential benefits, long-term adherence to KD poses challenges. Periodic KD implementation may thus benefit newly diagnosed overweight or obese patients with type 2 diabetes mellitus, aiding blood glucose and lipid management while promoting weight loss. KD is a high-fat and low-carbohydrate diet with a ratio of fat to carbohydrates and protein being 4:1 or 3:1, and thus, for peripheral tissues and the brain, fatty acids become the mandatory source of cellular energy. Ketone bodies have been used as the primary energy source during fasting. KD has been utilized as an effective treatment for refractory epilepsy since the 1920s. Evidence of the neuroprotective role of KD in diseases like epilepsy, stroke, traumatic brain injury, Alzheimer’s disease, and other neurological diseases has been noted. Since the 1960s, KD has become a popular method for obesity treatment. In addition, KD has been suggested as a potent anticancer therapy when used alone or as an adjuvant. KD may increase tumor cell sensitivity when combined with classic chemotherapy and radiotherapy. Thus, the probability that modifying the diet can help manage obesity, cancer, and chronic neurological disease without depending on pharmacological treatment and their serious side effects for a lifetime is promising and requires further investigation. KD holds promise as a potential adjunctive therapy in various neurological disorders, offering new avenues for treatment and neuroprotection. IF has shown potential in slowing the progression of neurodegenerative diseases such as Alzheimer's and Parkinson's by promoting antioxidant defense and suppressing inflammation. KD and IF show promise in cancer therapy by targeting altered cancer cell metabolism. Additionally, KD may enhance the effects of standard treatments like chemotherapy and radiotherapy. Some of the most robust reports of keto's possible benefits have come from glioblastoma, a very aggressive brain cancer. KD has also shown strong evidence for its effectiveness in weight loss, mainly attributed to its appetite-suppressing action in ketosis. However, long-term adherence to KD can be challenging, and periodic KDs may help manage blood glucose and lipid levels in overweight or obese patients with type 2 diabetes mellitus. Likewise, IF may be more effective than regular calorie restriction for achieving weight loss goals when combined with exercise programs. More prospective human studies are warranted to evaluate both KD and IF's potential therapeutic effectiveness and safety.

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.

The ubiquitin proteasome system (UPS) utilizes an orchestrated enzymatic cascade of E1, E2, and E3 ligases to add single or multiple ubiquitin-like molecules as post-translational modification (PTM) to proteins. Ubiquitination can alter protein functions and/ or marks ubiquitinated proteins for proteasomal degradation but deubiquitinases (DUBs) can reverse protein ubiquitination. While the importance of DUBs as regulatory factors in the UPS is undisputed, many questions remain on DUB selectivity for protein targeting, their mechanism of action, and the impact of DUBs on the regulation of diverse biological processes. Furthermore, little is known about the expression and role of DUBs in tumors of the human central nervous system (CNS). In this comprehensive review, we have used publicly available transcriptional datasets to determine the gene expression profiles of 99 deubiquitinases (DUBs) from five major DUB families in seven primary pediatric and adult CNS tumor entities. Our analysis identified selected DUBs as potential new functional players and biomarkers with prognostic value in specific subtypes of primary CNS tumors. Collectively, our analysis highlights an emerging role for DUBs in regulating CNS tumor cell biology and offers a rationale for future therapeutic targeting of DUBs in CNS tumors.

Autism Spectrum Disorder (ASD), a neurodevelopmental disorder characterized by persistent deficits in social interaction and communication manifests in early childhood and is followed by restricted and stereotyped behaviors, interests or activities in adolescence and adulthood (DSM-V). Although genetics and environmental factors have been implicated, the exact causes of ASD have yet to be fully characterized. New evidence suggests that dysbiosis or perturbation in gut microbiota (GM) and exposure to lead (Pb) may play important roles in ASD etiology. Pb is a toxic heavy metal that has been linked to a wide range of negative health outcomes including anemia, encephalopathy, gastroenteric diseases and more importantly cognitive and behavioral problems inherent to ASD. Pb exposure can disrupt GM, which is essential for maintaining overall health. GM, consisting of trillions of microorganisms, has been shown to play a crucial role in the development of various physiological and psychological functions. GM interacts with the brain in a bidirectional manner referred to as “Gut-Brain Axis (GBA).” In this review, following a general overview of ASD and GM, the interaction of Pb with GM in the context of ASD is emphasized. Potential exploitation of this interaction for therapeutic purposes is also touched upon.

Brain disorders pose a significant global healthcare challenge due to their complexity and profound impact on individuals and society. This review explores recent advancements in brain disease research, deepening our understanding and progress towards treatments. Technological innovations, like high-resolution imaging and optogenetics, play a pivotal role in illuminating cellular structures and dissecting neural circuits. Genetic analysis identifies dis-ease-associated genes and mutations, yet translating findings to clinical applications remains challenging. Epigenomics, transcriptomics, and proteomics provide molecular insights, un-covering disrupted pathways in conditions like Alzheimer's disease. Stem cell models elucidate developmental mechanisms, and immunotherapies, including CAR T cells, emerge as prom-ising strategies for brain cancers like glioblastoma. Genome editing tools, exemplified by CRISPR, enable precise modification of disease genes in models, deepening our understanding of pathogenesis. Multifaceted approaches integrating human studies, animal models, and bi-oinformatics propel the field forward. However, complexities persist, as disease specificity for cell types or brain regions remains an enigma, and genetic factors interact with environmental influences, highlighting disease intricacies. Ultimately, interdisciplinary efforts combining bi-ophysical and psychospiritual perspectives are essential to fully understand brain health and unlock transformative treatments for these debilitating disorders. A comprehensive under-standing of brain disorders is vital to improve the quality of life for millions and alleviate the global burden of neurological afflictions. Continued collaborative research will lead to an era of improved brain health worldwide.

Cyclin-dependent kinase-like 5 (CDKL5) deficiency disorder (CDD) is a rare neurodevelopmental disease caused by mutations in the X-linked CDKL5 gene. CDD is characterized by a broad spectrum of clinical manifestations, including early-onset refractory epileptic seizures, intellectual disability, hypotonia, visual disturbances, and autism-like features. The Cdkl5 knockout (KO) mouse recapitulates several features of CDD, including autistic-like behavior, impaired learning and memory, and motor stereotypies. These behavioral alterations are accompanied by diminished neuronal maturation and survival, reduced dendritic branching and spine maturation, and marked microglia activation. There is currently no cure or effective treatment to ameliorate the symptoms of the disease. Aerobic exercise is known to exert multiple beneficial effects in the brain, not only by increasing neurogenesis, but also by improving motor and cognitive tasks. To date, no studies have analyzed the effect of physical exercise on the phenotype of a CDD mouse model. In view of the positive effects of voluntary running on the brain of mouse models of various human neurodevelopmental disorders, we sought to determine whether voluntary daily running, sustained over a month, could improve brain development and behavioral defects in Cdkl5 KO mice. Our study showed that long-term voluntary running improved hyperlocomotion and impulsivity behaviors, and memory performance of Cdkl5 KO mice. This is correlated with increased hippocampal neurogenesis, neuronal survival, spine maturation, and inhibition of microglia activation. These behavioral and structural improvements were associated with increased BDNF levels. Given the positive effects of BDNF on brain development and function, the present findings support the positive benefits of exercise as an adjuvant therapy for CDD.

Neuroinflammation is considered to be a significant component in a range of neuropathologies. Unfortunately, whilst its role is well recognized, the options for therapeutic intervention are limited. As such, there is a need to identify novel targets in order to increase treatment options. Given its role as both a neurotransmitter and an immune modulator, substance P and its NK1 receptor have been widely studied as a potential therapeutic target. There is evidence that NK1 receptor antagonists may exert beneficial effects in a range of conditions, including traumatic brain injury and stroke. Blocking the NK1 receptor has been shown to reduce blood-brain barrier dysfunction, reduce cerebral oedema, and reduce the levels of pro-inflammatory cytokines. These actions are associated with improved survival and functional outcomes. The NK1 receptor has also been shown to be involved in the inflammatory reaction to CNS infection, and hence antagonist may have some benefit in reducing infection-driven inflammation. However, the NK1 receptor may also play a role in the host immune response to infection, and so here, the potential beneficial and detrimental effects need to be carefully balanced. As such, the purpose of this review is to provide a summary of the involvement of substance P in acute inflammation, particularly in the context of traumatic brain injury and stroke.

Preterm infants often experience frequent intermittent hypoxia (IH) episodes which is associated with neuroinflammation. We tested the hypotheses that early caffeine and/or non-steroidal in-flammatory drugs (NSAIDs) confer superior therapeutic benefits for protection against IH-induced neuroinflammation than late treatment. Newborn rats were exposed to IH or hy-peroxia (50% O2) from birth (P0) to P14. For early treatment, the pups were administered: 1) dai-ly caffeine citrate (Cafcit, 20 mg/kg IP loading on P0, followed by 5 mg/kg from P1-P14); 2) ke-torolac topical ocular solution in both eyes from P0 to P14; 3) ibuprofen (Neoprofen, 10 mg/kg loading dose on P0 followed by 5 mg/kg/day on P1 and P2); 4) caffeine+ketorolac co-treatment; 5) caffeine+ibuprofen co-treatment; or 6) equivalent volume saline. On P14, animals were placed in room air (RA) with no further treatment. For late treatment, pups received similar treatments from P15-P21 (caffeine and/or ketorolac), or P15-P17 (ibuprofen). RA control were similarly treated. At P21, whole brains were assessed for histopathology, apoptosis, mye-lination, and biomarkers of inflammation. IH caused significant inflammation, reduced mye-lination, and apoptosis in preterm rat brains, an effect that was improved predominantly with combined caffeine/NSAID early treatment. Early caffeine/NSAID co-treatment confers syner-gistic neuroprotection against IH-induced damage.

Brain-derived neurotrophic factor (BDNF) is a key molecule in promoting neurogenesis, dendritic and synaptic health, and neuronal survival, plasticity, and excitability, all of which are disrupted in neurological and cognitive disorders such as Alzheimer’s disease (AD). Extracellular aggregates of amyloid-β (Aβ) in the form of plaques and intracellular aggregates of hyperphosphorylated tau protein have been identified as major pathological insults in AD brain, along with immune dysfunction, oxidative stress, and other toxic stressors. Although aggregated Aβ and tau lead to decreased brain BDNF expression, early losses in BDNF prior to plaque and tangle formation may be due to other insults such as oxidative stress and contribute to early synaptic dysfunction. Physical exercise, on the other hand, protects synaptic and neuronal structure and function, with increased BDNF as a major mediator of exercise-induced enhancements in cognitive function. Here, we review recent literature on mechanisms behind exercise induced BDNF upregulation and its effects on improving learning and memory and on Alzheimer’s disease pathology. Mechanisms include elevations in peripheral BDNF-inducing hormones such as osteocalcin, FNDC5/irisin, and lactate. The fundamental mechanisms of how exercise impacts BDNF and cognition are unclear but are a prerequisite to developing new biomarkers and therapies to delay or prevent cognitive decline.

The present review aimed to identify through what means neurologic injury can predispose individuals to Post-Traumatic Stress Disorder (PTSD). In recent years, comprehensive studies have helped to clarify which structures in the central nervous system (CNS) that, when damaged, lead to distinct PTSD symptoms–namely dissociative reactions or flashbacks. Our review narrowed its focus to three common neurologic injuries including traumatic brain injury (TBI), subarachnoid hemorrhage (SAH), and stroke. Beyond discussing the potential mechanisms by which neurotrauma may lead to PTSD, we summarized our current understanding of the pathophysiology of the disorder and discussed predicted associations between the limbic system and PTSD. In particular, the role of noradrenergic neuromodulatory signaling on the HPA axis as it pertains to fear memory recall needs to be further explored to better understand its effects on limbic structures in PTSD patients. This paper also described how damage to the CNS can alter the function of the limbic system and result in characteristic symptoms of PTSD like intrusive memories and acute psychological distress. Further, our review intended to draw attention to a lack of PTSD prognosis in TBI, SAH, and stroke patients who could benefit from early treatment. PTSD symptoms often compound with pre-existing issues further deteriorating health outcomes for these patients. It is ultimately our goal to clarify the relationship between neurotrauma and PTSD such that earlier diagnoses and appropriate treatment are observed in clinic.

Three-quarters of a million babies are born extremely preterm (< 28 weeks’ gestation) world-wide with devastating outcomes: 20% die in the newborn period, a further 35% develop bronchopul-monary dysplasia (BPD) and 10% suffer from cerebral palsy. Pioglitazone, a Peroxisome Proliferator Activated Receptor Gamma (PPARγ) agonist, may reduce the incidence of BPD and improve neurodevelopment in extreme preterm babies. Pioglitazone exerts an anti-inflammatory action mediated through Nuclear Factor-kappa B repression. PPARγ signalling is underactive in preterm babies as adiponectin remains low during the neonatal pe-riod. In newborn animal models, pioglitazone is shown to be protective against BPD, necrotising en-terocolitis, and lipopolysaccharide-induced brain injury. Single Nucleotide Polymorphisms of PPARγ are associated with inhibited preterm brain development and impaired neurodevelop-ment. Pioglitazone was well tolerated by the foetus in reproductive toxicology experiments. Bladder cancer, bone fractures, and macular oedema seen rarely in adults may be avoided with a short treatment course. Other effects of pioglitazone including improved glycaemic control and lipid metabolism may provide added benefit in prematurity. Currently, there is no formulation of pioglitazone suited for administration to preterm babies A liquid formulation of pioglitazone needs to be developed before clinical trials. The potential benefits are likely to outweigh any anticipated safety concerns.

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.

Emotion recognition and social inference impairments are well-documented post-traumatic brain injury (TBI) yet the mechanisms underpinning these are not fully understood. We examined dynamic emotion recognition, social inference abilities, and eye fixation patterns between adults with and without TBI. Eighteen individuals with TBI and 18 matched non-TBI participants were recruited and underwent all three components of The Assessment of Social Inference Test (TASIT). The TBI group were less accurate in identifying emotions compared to the non-TBI group. Individuals with TBI also scored lower when distinguishing sincere and sarcastic conversations but scored similarly to those without TBI during lie vignettes. Finally, those with TBI also had difficulty understanding the actor’s intentions, feelings, and beliefs compared to participants without TBI. No group differences were found for eye fixation patterns and there were no associations between fixations and behavioural accuracy scores. This conflicts with previous studies and might be related to an important distinction between static and dynamic stimuli. Visual strategies appeared goal- and stimulus-driven, with attention being distributed to the most diagnostic area of the face for each emotion. These findings suggest that low-level visual deficits may not be modulating emotion recognition and social inference disturbances post-TBI.

Abstract: In recent years, low frequency (LF) electroencephalogram (EEG) signals have been decoded to obtain kinematic trajectories with the aim of achieving closed loop natural control. However, decoded trajectories suffer variability and low correlation against the measured movement. This paper suggests that if EEG features of motor intents are directly associated with fixed points along a given range of motion, then the natural kinematic parameters can be quantified. A novel classification method is proposed to evaluate this hypothesis along with equations for obtaining the movement parameters (velocity, acceleration). Furthermore, this implies that the force of an end-effector and work done in moving the end-effector may be computed, leading to natural control of EEG-based robotic arms and neuroprostheses. Finally, expectations are that combining the proposed method with existing classification methods will increase the accuracy and scalability of brain-computer interface (BCI) applications.

Since there are no morphological clues capable of making a pathologist suspect a possible mammary origin of a metastatic lesion without adequate clinical information, the histologic diagnosis of brain metastasis from BC is still based on the immunohistochemical expression of mammary gland markers such as GATA-3, ERs, PgRs and HER-2. The present retrospective study aimed to select purely morphological features capable to suggest the mammary origin of a metastatic carcinoma to the brain. The following histological features were collected on a series of 30 cases of brain metastases from breast cancer:(i) solid growth pattern; (ii) presence of comedonecrosis; (iii) glandular differentiation. Our results showed that most cases histologically exhibited solid growth pattern with at least focal comedonecrosis, producing an overall morphology closely reminiscent of mammary high-grade ductal carcinoma in situ. Although the above-mentioned morphological parameters are not strictly specific to a mammary origin, they may have an important diagnostic utility in leading pathologists to suspect a possible breast primary tumor and to include GATA-3, ERs, PgRs and HER-2 to the immunohistochemical panel.

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.

Abstract: Autism spectrum disorders (ASDs) are complex, lifelong, neurodevelopmental conditions of largely unknown cause. The global prevalence of autism has increased twentyfold to thirtyfold since the earliest epidemiologic studies were conducted in the late 1960s and early 1970s. Recent reports agree on the association of ASD with the alteration of the microbiome (dysbiosis), which raises the possible role of external factors. Our study aimed at identifying antibiotic classes that might be associated with the development of ASD-related dysbiosis either promoting or inhibiting the process. Statistical comparison was made between the average yearly consumption of different antibiotic classes (1997-2020) and the number of individuals living with ASD estimated for 2023/100000 population in 30 European countries and the results were statistically analyzed. Tetracycline (J01A) showed significant positive (promoting) association with the prevalence of ASD (Pearson r: 0.373, p: 0.043. OR: 1.312, CI95%: 0.995-1.791, p: 0.065) and narrow-spectrum, beta-lactamase resistant penicillin (J01CF) (Pearson r: 0.524, p: 0.003, OR: 3.240, CI95%: 1.710-8.853, p: 0.004, Kruskal-Wallis p: 0.032). Mild, negative (inhibitory) association was observed with broad-spectrum, beta-lactamase sensitive penicillin (J01CA) (Pearson r: -0.278, p: 0.157, OR: 0.808, CI95%: 0649-0957, p: 0.028) and narrow-spectrum, beta-lactamase-sensitive penicillin (J01CE) (Pearson p: -0.032, r: 0.865, OR: 0.725, CI95%: 0.543-0.885, p: 0,009). Our findings strongly support the animal experiments when penicillin-exposed newborn mice developed "autism-like" behavior.

The acetylcholinesterase-inhibitory potential of the oleanane-type triterpenes and their glycosides from the Terminalia arjuna (Combreatceae) bark, i.e. arjunic acid, arjunolic acid, arjungenin, arjunglucoside I, sericic acid, and arjunetin, is presented. The studies are based on the in silico pharmacokinetic and biomimetic studies, the acetylcholinesterase (AChE) inhibitory activity tests, and the molecular docking research. Based on the calculated pharmacokinetic parameters, arjunetin and arjunglucoside I are indicated as able to cross the blood-brain barrier. The compounds of interest exhibit marked acetylcholinesterase inhibitory potential, which was tested in the TLC bioautography test. The longest time to reach brain equilibrium is observed for both the arjunic and arjunolic acids and the shortest one for arjunetin. All compounds exhibit high and relatively similar magnitude of binding energies, varying from ca. -15 to -13 kcal/mol. The superposition of the most favorable positions of all ligands interacting with AChE is analyzed. The correlation between the experimentally determined IC50 values and the steric parameters of the molecules is investigated. The inhibition of the enzyme by the analyzed compounds shows their potential to be used as cognition enhancing agents. For the most potent compound (arjunglucoside I; ARG), the kinetics of AChE inhibition is tested. The Michaelis–Menten constant (Km) for the hydrolysis of the acetylthiocholine iodide substrate was calculated to be 0.011 mM.

Astragaloside IV (AIV) – triterpenoid saponin from the Astragalus mongholicus roots with the proved acetylcholinesterase (AChE)-inhibitory capability was used as the substance with the potential to attenuate memory impairment. Scopolamine (SCOP), antagonist of muscarinic cholinergic receptors and lipopolysaccharide (LPS), neuroinflammation inducer were used to impair memory processes in the passive avoidance (PA) test in mice. This memory impairment in the SCOP-treated mice was attenuated by the earlier intraperitoneal (ip) administration of AIV in the dose of 25 mg/kg. The reduction of memory impairment by LPS was not observed, therefore AIV does not reverse memory impairments through the anti-inflammatory mechanisms. All the studied doses of AIV did not affect basic locomotor activity of mice. As a result of the post-mortem analysis of mice body tissues, the largest content of AIV was determined in the kidneys, then in the spleen, liver and the smallest one in brain by mass spectrometry.

Abstract: The brain endothelial cell (BEC) glycocalyx (ecGCx) is a BEC surface coating consisting of a complex interwoven polysaccharide (sweet husk) mesh-like network of membrane-bound proteoglycans, glycoproteins, and glycosaminoglycans (GAGs) covering the apical luminal layer of the brain endothelial cells. The ecGCx may considered as the 1st barrier of a tripartite blood-brain barrier (BBB) consisting of 1) ecGCx; 2) BECs; (3) extravascular compartment of pericytes, extracellular matrix, and perivascular astrocytes, Perturbations of this barrier allow for increased permeability in the postcapillary venule that will be permissive to both fluids, solutes, and proinflammatory peripherally-derived leukocytes into the perivascular spaces (PVS) to result in enlargement as well as increased neuroinflammation. The ecGCx is known to have multiple functions, which include its physical and charge barrier, mechanical transduction, regulation of vascular permeability, modulation of inflammatory response, and anticoagulation functions. This review discusses each of the listed functions in detail and utilizes multiple transmission electron micrographs and illustrations to allow for a better understanding of the ecGCx structural and functional roles as it relates to enlarged perivascular spaces (EPVS). This is the 5th review of a series quintet that discuss the importance of EPVS from the perspective of the cells of brain barriers. Attenuation and/or loss of the ecGCx results in brain barrier disruption with increased permeability to proinflammatory leukocytes, fluids and solutes, which accumulate in the postcapillary venule perivascular spaces. This accumulation results in obstruction and results in EPVS with impaired waste removal of the recently recognized glymphatic system. Importantly, EPVS are progressively being regarded as a marker of cerebrovascular and neurodegenerative pathology.

Intracortical microelectrode arrays (MEAs) can be used in a range of applications, from basic neuroscience research to providing an intimate interface with the brain as part of a Brain-Computer Interface (BCI) system aimed to restore function for people living with neurological disorders or injuries. Unfortunately, MEAs tend to fail prematurely, leading to a loss in functionality for many applications. An important contributing factor in MEA failure is oxidative stress resulting from chronically inflammatory-activated microglia and macrophages releasing reactive oxygen species (ROS) around the implant site. Antioxidants offer a means for mitigating oxidative stress and improving tissue health and MEA performance. Here, we investigate using the clinically available antioxidant dimethyl fumarate (DMF) to reduce the neuroinflammatory response and improve MEA performance in a rat MEA model. Daily treatment of DMF for 16 weeks resulted in a significant improvement in the recording capabilities of MEA devices during the sub-chronic (Weeks 5-11) phase (42% active electrode yield vs. 35% for control). However, these sub-chronic improvements were lost in the chronic implantation phase, as a more exacerbated neuroinflammatory response occurs in DMF-treated animals by 16 weeks post-implantation. Yet, neuroinflammation was indiscriminate between treatment and control groups during the sub-chronic phase. Although worse for chronic use, a temporary improvement (&lt;12 weeks) in MEA performance is meaningful. Providing short-term improvement to MEA devices using DMF can allow for improved use for limited-duration studies. Further efforts should be taken to explore the mechanism behind a worsened neuroinflammatory response at the 16-week time point for DMF-treated animals to assess its usefulness to specific applications.

As the human-body controls depend on the brain neuro current, here assay is related to thinking nerve detection. For this purpose, the brain current was analyzed by electrochemical three-electrode systems using 0.1-mm micro wire in vivo probe, which probe was made by using carbon nanotube paste coated needle type. Here working electrode was inserted in the rat brain’s muscle core with a 0.3-mm-diameter needle type Ag/AgCl Cl-coated Ag wire reference, and counter electrode of 0.1-mm-diameter Pt micro needle was inserted 5 mm deep into the in vivo muscle skin, under anesthesia with 2.0 ~ -2.0 V potential windows, 50 mv/s cyclic scan and 1.0x10-5A chrono amperometric sensitivity on the body systems. Under the optimum conditions, diagnostic application was performed to such as smell signal, muscular strength, five sense assay and thinking neuro current.

Long Covid is a heterogeneous clinical condition in which Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and brain fog stand out among the different clinical symptoms and syndromes. The cerebral metabolic alterations and neuroendocrine disorders seem to constitute an important part of Long Covid. Given the substantial lack of drugs and effective therapeutic strategies, hypothalamic phospholipid liposomes which have been on the market for several years as adjuvant therapy of cerebral metabolic alterations resulting from neuroendocrine disorders, can be taken into consideration in an overall therapeutic strategy that aims to control the Long Covid associated symptoms and syndromes. Their pharmacological mechanisms and clinical effects strongly support their usefulness in Long Covid. Our initial clinical experience corroborates this rationale. Further research is imperative in order to obtain robust clinical evidence.

Eutherians have 11 retrotransposon Gag-like (RTL)/sushi-ichi retrotransposon homolog (SIRH) genes presumably derived from a certain retrovirus. Accumulating evidence indicates that the RTL/SIRH genes play a variety of roles in the current mammalian developmental system, such as in the placenta, brain and innate immune system in a eutherian-specific manner. It has been shown that the functional role of Paternally Expressed 10 (PEG10) in placental formation is unique to the therian mammals, as are the eutherian-specific roles of PEG10 and PEG11/RTL1 in maintaining the fetal capillary network and the endocrine regulation of RTL7/SIRH7 (aka Leucine Zipper Down-Regulated in Cancer 1 (LDOCK1)) in the placenta. In the brain, PEG11/RTL1 is expressed in the corticospinal tract and hippocampal commissure, mammalian-specific structures, and in the corpus callosum, a eutherian-specific structure. Unexpectedly, at least three RTL/SIRH genes, RTL5/SIRH8, RTL6/SIRH3 and RTL9/SIRH10, play important roles in combating a variety of pathogens, viruses, bacteria and fungi, respectively, suggesting that the innate immunity system of the brain in eutherians has been enhanced by the emergence of these new components. In this review, we will summarize the function of 10 out of the 11 RTL/SIRH genes and discuss their roles in eutherian development and evolution.

This article presents a study on brain tumor detection using the VGG-16 model, a convolutional neural network known for its performance in computer vision tasks. The aim of the study is to classify magnetic resonance imaging (MRI) images and accurately identify the presence of brain tumors. The dataset used consists of brain tumor MRI images, categorized into two classes: "NO" (no tumor) and "YES" (tumor). The methodology involves setting up the environment, importing and preprocessing the data, building the VGG-16 model, and evaluating its performance using metrics such as accuracy, precision, and recall. The results demonstrate an accuracy of approximately 88% on the validation set and 80% on the test set, indicating the potential of the VGG-16 model in supporting healthcare professionals in diagnosing brain tumors. The study contributes to the field of medical image analysis and offers insights into the application of deep learning for brain tumor detection.

The pathogen Cryptococcus neoformans is a major cause of fungal meningitis in humans. As with other melanotic microorganisms associated with human diseases, the cell wall-associated melanin of C. neoformans is a major virulence factor that contributes to its ability to evade host immune responses. The levels of melanin substrate and the regulation of melanin formation could be influenced by the microbiota-gut-brain axis. Moreover, recent studies show that C. neoformans infection causes dysbiosis in the human gut microbiome. In this review, we discuss the potential association between cryptococcal meningitis and the gut microbiome. Additionally, we emphasize the promising prospects of targeting the gut microbiome as a means of diagnosing and treating this debilitating disease.

Background: Abdominal migraine (AM) is a clinical diagnosis specified by Rome IV and ICHD III as a functional gastrointestinal disease (FGID) and a migraine associated syndrome, respectively. AM is undiagnosed and undertreated, and thus far the FDA has not approved any drug for AM treatment. We and others showed that changes in the kynurenine (KYN) pathway of tryptophan (TRP) metabolism played an important role in the pathogenesis and treatment of FIGDs. Changes in the KYN pathway were shown in migraine. Findings: Abdominal migraine reflects impairments in communication within the gut-brain axis. Treatment approaches have not been sufficiently documented and are based on experience of physicians, presenting personal rather than evidence-based practice and including efficacy of some drugs used in adult migraine. Non-pharmacological treatment of AM is aimed preventing or ameliorating AM triggers. Modulations within the KYN pathway of TRP metabolism induced by changes in TRP content in the diet, may ameliorate FGIDs and support their pharmacological treatment. Pharmacological manipulations of brain KYNs in animals have brought promising results for clinical applications. Conclusions: In conclusion, controlled placebo-based clinical trials with dietary manipulation to adjust the amount of the product of the KYN pathway of TRP metabolism are justified in children and adolescents with AM. Further preclinical studies are needed to establish details of these trials.

Depression is one of the psychiatric disorders characterized by anxiety, pessimism, and suicidal tendencies, which seriously affect the quality of life of patients and their families. In this paper, we used polynomial-based kernel Granger causality values as network node connectivity indicators to construct brain networks for 5 depressed patients and 11 healthy individuals’ magnetoencephalogram(MEG) under positive, neutral, and negative emotional stimuli, respectively, and found that depressed patients had closer information exchange between frontal and occipital regions compared to healthy individuals and other brain regions, and fewer causal connections in parietal and central regions. Further analysis of the topological properties of the network revealed that depressed patients had higher mean degrees under negative stimuli (p=0.008)and lower mean clustering coefficients than healthy individuals(p=0.034). Comparing the mean degree and mean clustering coefficient of the same sample under different emotional stimuli, we found that depressed patients had the greater mean degree and mean clustering coefficient under negative stimuli than neutral and positive stimuli. We also found that patients’ feature path lengths under negative and neutral stimuli significantly deviated from small-world attributes. The results suggest that analysis of nuclear Granger causality-based brain networks can effectively characterize depression pathology.

Postural instability (PI) in Parkinson’s disease (PD) exposes patients to increased risk of falls (RF). Although dopaminergic therapy and deep brain stimulation (DBS) improve motor performance in advanced PD patients, their effects on PI and RF are not clear. PI and RF were assessed by a stabilometric platform in 6 advanced PD patients. Patients were evaluated on and off dopaminergic medication and four DBS conditions: bilateral-DBS, DBS of the more- or less-affected side and DBS-off. Dopaminergic medication alone worsened PI and RF, DBS alone worsened RF, and no medication/DBS combination produced an improvement in postural control with respect to the OFF-medication/DBS-off condition. When ON-medication, PI and RF significantly improved after turning the DBS on, regardless of medication condition. Among DBS conditions, bilateral-DBS provided the maximal improvement of PI and RF when ON medication, and minimal worsening of PI and RF when OFF medication, whereas patients performed worse when in most-affected side DBS condition. These results can help in developing the best therapeutic strategy for postural disorders in patients with advanced PD.

Nowadays, brain signal processing is performed rapidly in various brain-computer interface (BCI) applications. Most researchers focus on developing new methods for the future or improving the basic implemented models to identify the optimum standalone feature set. Our research focuses on four ideas. One of them introduces future communication models, and the others are for improving old models or methods. These are: 1) new communication imagery model instead of speech imager using the mental task: Due to speech imagery is very difficult, and it is impossible to imagine sound for all of the characters in all of the languages. Our research introduces a new mental task model for all languages that call Lip-sync imagery. This model can use for all characters in all languages. This paper implemented two lip-sync for two sounds, characters or letters. 2) New combination Signals: Selecting an inopportune frequency domain can lead to inefficient feature extraction. Therefore, domain selection is so important for processing. This combination of limited frequency ranges proposes a preliminary for creating Fragmentary Continuous frequency. For the first model, two s intervals of 4 Hz as filter banks were examined and tested. The primary purpose is to identify the combination of filter banks with 4Hz (scale of each filter bank) from the 4Hz to 40Hz frequency domain as new combination signals (8Hz) to obtain well and efficient features using increasing distinctive patterns and decreasing similar patterns of brain activities.3) new supplement bond graph classifier for SVM classifier: When SVM linear uses in very noisy, the performance is decreased. But we introduce a new bond graph linear classifier to supplement SVM linear in noisy data. 4) a deep formula recognition model: it converts the data of the first layer into a formula model (formula extraction model). The main goal is to reduce the noise in the subsequent layers for the coefficients of the formulas. The output of the last layer is the coefficients selected by different functions in different layers. Finally, the classifier extracts the root interval of the formulas, and the diagnosis does based on the root interval. For all of the ideas achieved the results of implementing methods. The results are between 55% to 98%. Less result is 55% for the deep detection formula, and the highest result is 98% for new combination signals.

Neurodegenerative diseases encompass a broad spectrum of profoundly disabling disorders that impact millions of individuals globally. While their underlying causes and pathophysiol-ogy display considerable diversity and remain incompletely understood, a mounting body of evidence indicates that the disruption of blood-brain barrier (BBB) permeability, resulting in brain damage and neuroinflammation, constitutes a shared characteristic among them. Con-sequently, targeting the BBB has emerged as an innovative therapeutic strategy for address-ing neurological diseases. Within this review, we not only explore the neuroprotective, neu-rotrophic, and immunomodulatory benefits of mesenchymal stem cells (MSCs) in combating neurodegeneration but also delve into their recent role in modulating the BBB. We will delve into the cellular and molecular mechanisms through which MSC treatment impacts primary age-related neurological disorders like Alzheimer’s disease, Parkinson’s disease, and stroke as well as immune-mediated conditions such as multiple sclerosis. Our focus will center on how MSCs participate in the modulation of cell transporters, matrix remodeling, stabilization of cell-junction components, and restoration of BBB network integrity in these pathological con-texts.

Complex interactions between gene variants and environmental risk factors underlie the pathophysiological pathways in major psychiatric disorders. Autism Spectrum Disorder is a psychiatric condition in which susceptible alleles along with epigenetic memories contribute to the mutational landscape of the ailing brain. The present work reviews recent evolutionary, molecular, and epigenetic mechanisms potentially linked to the etiology of autism. First, we present a clinical vignette to describe clusters of maladaptive behaviors frequently diagnosed in autistic patients. Next, we microdissect brain regions pertinent to the nosology of autism as well as cell networks from the bilateral body plan. Lastly, we catalog a number of pathogenic environments associated with disease risk factors. This set of perspectives provides emerging insights into the dynamic interplay between epigenetic and environmental variation in the development of Autism Spectrum Disorders.

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&lt;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.

Brain plasticity is induced by learning during wakefulness and is consolidated during sleep. But the molecular mechanisms involved are poorly understood and their relation to experience-dependent changes in brain activity remains to be clarified. Localized mRNA translation is im-portant for the structural changes at synapses supporting brain plasticity consolidation. Sleep has been shown activate the translation mTOR pathway, via phosphorylation of 4E-BPs, during brain plasticity, but whether this activation is specific to synapses is not known. We investigated this question using acute exposure of rats to an enriched environment (EE). We measured brain activity with EEGs and 4E-BPs phosphorylation at cortical and cerebellar synapses with Western Blot. Sleep significantly increased the conversion of 4E-BPs to its hyperphosphorylated form at synapses, especially after EE exposure. EE exposure increased oscillations in the alpha band dur-ing active exploration and in the theta to beta (4-30Hz) range, as well as spindle density, during NREM sleep. Theta activity during exploration and NREM spindle frequency predicted changes in 4E-BPs hyperphosphorylation at synapses. Our results provide a link between EEG and mo-lecular markers of plasticity across wake and sleep.

When “hijacked” by compulsive behaviors that affect the reward and stress centers of the brain, functional changes in dopamine circuitry occur as the consequence of pathological brain adaptation. As a brain explanans for mental health, with a central functional role in behavioral regulation from healthy reward seeking to pathological adaptation to stress in response to adversity, we may use dopamine regulation in interaction with other brain mechanisms, as discussed herein, to gather a deeper insight into environmentally triggered mental health changes to understand, for example, specific behavioral changes observed during and after the COVID-19 pandemic. Pandemic-related adversities, the stresses they engendered, and the long lockdown periods where people had to rely on digital tools to get feed-back rewards via the internet can be seen as the major triggers of changes in motivation and reward seeking behavior worldwide. The pathological adaptation of dopamine-mediated reward circuitry in the brain offers a highly plausible explanation why, when pushed by fate and circumstance into a physiological brain state of anti-reward, human behavior and mental health changes almost inevitably depending on individual vulnerability to stress. A unified conceptual account that places dopamine function at the centre of the current global mental health context is proposed.

Brain hemispheres develop rather symmetrically except in the case of pathology or intense training. As school experience is a form of training, the current study tested the influence of pedagogy on morphological development through the cortical thickness (CTh) asymmetry index (AI). First, we compared CTh AI of 111 students aged 4 to 18 with 77 adults aged > 20. Second, we investigated CTh AI in the students, as a function of schooling background (Montessori or traditional). At the whole-brain level, CTh AI was not different between the adult and student groups, even when controlling for age. However, the pedagogical experience was found to impact CTh AI in the temporal lobe, within the parahippocampal (PHC) region. The PHC has a functional lateralization, with the right PHC having a stronger involvement in spatiotemporal context encoding, while the left PHC is involved in semantic encoding. We observed CTh asymmetry toward the left PHC for participants enrolled in Montessori schools and toward the right for participants enrolled in traditional schools. As these participants were matched on age, intelligence, home life, and socioeconomic conditions, we interpret this effect found in memory-related brain regions to reflect differences in learning strategies. Pedagogy modulates how new concepts are encoded, with possible long-term effects on knowledge transfer.

Non-small-cell lung cancer (NSCLC) is the second most common cancer worldwide, resulting in 1.8 million deaths/year. Most of the patients are diagnosed with a metastatic disease. Central Nervous System is one of the major metastatic sites. Brain metastases are associated with severe neurological symptoms, shorter survival and worst clinical outcomes. Brain radiotherapy and systemic oncological therapies are currently used for controlling both cancer progression and neurological symptoms. Brain radiotherapy includes stereotactic brain ablative radiotherapy (SBRT) or whole brain radiotherapy (WBRT). SBRT is applied for single or multiple (≤ 4) small lesions (&lt; 3 cm), while WBRT represents the best treatment choice in case of multiple and large brain metastases. In both cases radiotherapy application can represent an overtreatment causing severe toxicities without achieving a significant clinical benefit. So far, some scores have been proposed to define the potential clinical benefits derived from brain radiotherapy. However, most of them are not well validated into clinical practice. In this article, by presenting a clinical case of a patient with advanced NSCLC carrying a BRAFV600E mutation and brain metastases, we review the variables as well as the potential applicable scores to be considered in order to predict clinical outcomes and benefits from brain radiotherapy in patients with NSCLC and brain metastases.

Abstract: Accurately predicting a fetus's gestational age (GA) is of utmost importance in prenatal care. This study aimed to develop an artificial intelligence (AI) model that can automatically predict GA using biometric measurements derived from fetal brain mag-netic resonance imaging (MRI). Additionally, we aimed to assess the significance of con-sidering different references when interpreting GA predictions. To achieve this, we obtained measurements such as Biparietal Diameter (BPD), Fron-to-occipital Diameter (FOD), and Head Circumference (HC) from a dataset comprising 52 normal fetal MRI cases with T2 Haste sequences from Rush University. Both manual and AI-based methods were utilized to acquire these measurements. We also employed three reference papers (Garel, Freq, and Bio) for comparison purposes. The results demonstrated a strong correlation between manual and AI measure-ments, indicating consistency between the two methods. The AI-based measurement of HC exhibited a higher correlation with actual values compared to BPD, FOD, and correct-ed BPD (BPDC). When comparing these measurements with GA in the Picture Archiving and Communication System (PACS), the differences varied depending on the reference used. Specifically, the differences ranged from 0.47 to 2.17 weeks for BPD, 0.46 to 2.26 weeks for FOD, and 0.75 to 1.74 weeks for HC. Furthermore, the Pearson correlation coeffi-cient analysis revealed that all correlation coefficients between PACS records and GA pre-dictions using different references were greater than 0.97. In conclusion, the AI model based on fetal brain MRI accurately predicts GA by uti-lizing BPD, FOD, and HC measurements. The AI approach, which involves combining line segments to calculate fetal head circumference, offers improved accuracy and con-venience compared to manual estimation. This study underscores the potential of AI models in accurately estimating gestational age and highlights their utility in prenatal care. By integrating AI as a valuable tool in prenatal care, we can enhance the accuracy, ef-ficiency, and decision-making involved in assessing fetal development and monitoring pregnancies using MRI measurements.

A single paragraph of about 200 words maximum. Electroencephalography (EEG) accumulates the electrical activities of human brain. It is an easy and cost effective tool to characterize motor imagery (MI) task used in brain computer interface (BCI) implementation. The MI task is represented by short time trial of multichannel EEG. In this paper, the raw EEG is decomposed into a finite set of narrowband signals obtained from individual EEG channels using Fourier transformation based bandpass filter. Each of the subband signals represents narrowband rhythmic components which characterize the brain activities related to motor imagery. The subband signals are arranged to extent the dimension of EEG trial in spatial domain. The spatial features are extracted from the set of extended trials using common spatial pattern (CSP). An optimum number of features are used to classify the motor imagery tasks represented by EEG trials. Artificial neural network is used to classify MI tasks. The performance of the proposed method is evaluated using two publicly available benchmark datasets. The experimental results show that it performs better than the recently developed algorithms.

Background: This review aims to explore the regulatory mechanism of microglial exosomes, particularly focusing on the role of miR-124-3p, in modulating neuroinflammation and promoting neuronal repair following traumatic brain injury (TBI). Methods: Multiple studies investigating the impact of microglial exosomal miRNAs, specifically miR-124-3p, on injured neurons and brain microvascular endothelial cells (BMVECs) in the context of TBI were reviewed. Results: Animal models of TBI, in vitro cell culture experiments, RNA sequencing analysis, and functional assays were employed to elucidate the mechanisms underlying the effects of miR-124-3p-loaded exosomes on neuroinflammation and neuronal repair. The increased expression of miR-124-3p in microglial exosomes after TBI inhibited neuronal inflammation and promoted neurite outgrowth. This effect was achieved by promoting the anti-inflammatory M2 polarization of microglia, suppressing mTOR signaling through downregulation of PDE4B, and inducing autophagy in BMVECs. These actions collectively contributed to neuroprotection, reduced blood-brain barrier leakage, and improved neurologic outcomes in animal models of TBI. Conclusion: Microglial exosomes, particularly those carrying miR-124-3p, have emerged as promising candidates for therapeutic interventions in TBI. These exosomes exhibit neuroprotective effects, attenuate neuroinflammation, and promote neuronal repair and plasticity. Targeting miR-124-3p and utilizing microglial exosomes as therapeutic agents hold great potential for future clinical translation in TBI management. However, further research is required to fully elucidate the underlying mechanisms and optimize their delivery strategies for effective treatment in human TBI cases.

Teachability has been extensively studied under the context of making industrial robots to be programmable and reprogrammable. However, it is only recently that the artificial intelligence (AI) research community is accelerating the research works with the objective of making humanoid robots and many other robots to be teachable under the context of using natural languages. We human beings spend many years to learn knowledge and skills despite our extraordinary mental capabilities of being teachable with the use of natural languages. Therefore, if we would like to develop human-like robots such as humanoid robots, it is inevitable for us to face the issue of making future humanoid robots to be teachable with the use of natural languages as well. In this paper, we present the key details of a top-down design for achieving a teachable mind which consists of two major processes: the first one is the process which enables humanoid robots to gain innate mental capabilities of transforming incoming signals into meaningful crisp data, and the second one is the process which enables humanoid robots to gain innate mental capabilities of undertaking incremental and deep learning with the main focus of associating conceptual labels in a natural language to meaningful crisp data. These two processes consist of the two necessary and sufficient conditions for future humanoid robots to be teachable with the use of natural languages. In addition, this paper outlines a very likely new finding underlying human brain’s neural systems as well as the obvious mathematics underlying artificial deep neural networks. These outlines provide us the strong reason to separate the study of mind from the study of brain. Hopefully, the content discussed in this paper will help the AI research community to venture into the right direction which is to make future humanoid robots, non-humanoid robots, and many other systems to achieve human-like self-intelligence at cognitive level with the use of natural languages.

Chronic gastroduodenal symptoms are prevalent worldwide, and there is a need for new diagnostic and treatment approaches. Several overlapping processes may contribute to these symptoms, including gastric dysmotility, hypersensitivity, gut-brain axis disorders, gastric outflow resistance, and duodenal inflammation. Gastric Alimetry® (Alimetry, New Zealand) is a non-invasive test for evaluating gastric function that combines body surface gastric mapping (high-resolution electrophysiology) with validated symptom profiling. Together, these complementary data streams enable important new clinical insights into gastric disorders and their symptom correlations, with emerging therapeutic implications. A comprehensive database has been established, currently comprising >2,000 Gastric Alimetry tests, including both controls and patients with various gastroduodenal disorders. From studies employing this database, this pa-per presents a systematic methodology for Gastric Alimetry test interpretation, together with an extensive supporting literature review. Reporting is grouped into four sections: Test Quality, Spectral Analysis, Symptoms, and Conclusions. This review compiles, assesses, and evaluates each of these aspects of test assessment, with discussion of relevant evidence, example cases, limitations, and areas for future work. The resultant interpretation methodology is recommended for use in clinical practice and research to assist clinicians in their use of Gastric Alimetry as a diagnostic aid, and is expected to continue to evolve with further development.

Background: Post-delivery period could be characterized by psychological distress (e.g., anxiety, sadness, and irritability), leading to post-partum depression (PPD). Objective: The present clinical study assess the effect of probiotic supplementation containing Limosilactobacillus reuteri PBS072 and Bifidobacterium breve BB077 (4x10⁹ CFU/day) on mother’s mood and breastfeeding quality during the first trimester after delivery. Methods: A Randomized Double Blind Controlled (RDBPC) trial has been carried out in 200 healthy new mothers divided into an active group taking a supplement containing Limosilactobacillus reuteri PBS072 and Bifidobacterium breve BB077 (4x10⁹ CFU/day) plus multivitamins, and a control group (multivitamin complex only) for 90 days. Symptoms related to maternal depression and breastfeeding quality were evaluated at days 45 and 90 by Edinburgh Postnatal Depression Scale (EPDS) and Breastfeeding Self-Efficacy Scale Short-Form (BSES-SF). Results: At days 45 and 90, probiotic treatment significantly ameliorated the mothers’ mood compared to the control treatment (p<0.001). Likewise, breastfeeding quality and baby’s cries significantly improved in the probiotic group (p<0.001). Conclusions: Microbiota alterations could influence post-delivery woman’s mental state. According to our results, L. reuteri PBS072 and B. breve BB077 are potential candidates able to improve stress resilience in the post-partum period.

Bone marrow mononuclear cells (BMMNCs) have emerged as a potential therapeutic strategy for various incurable conditions including autism spectrum disorder (ASD). To study its safety and efficacy, we analyzed 1011 patients who underwent intrathecal administration of autologous BMMNCs along with neurorehabilitation. At mean follow-up of 19.3 months after intervention, 90.6% patients showed overall improvement. Improvements were observed in attention concentration, command following, eye contact, sitting tolerance, social interaction, hyperactivity, communication, speech, aggressiveness, stereotypical and self-injurious behavior. Statistically significant changes were observed in scores of Indian Scale of Autism Assessment and Childhood Autism Rating Scale (p<0.05). On subgroup analysis, improvements were recorded irrespective of age and disease severity and better outcome was observed in patients who took multiple doses of cell therapy compared to single dose. Comparative Brain PET-CT scan of 401 patients showed improved brain metabolism after the intervention. No major adverse events were reported. Only 9 out of 1011 patients experienced seizures which were managed using medications. 4 out of 9 had history of seizures while 5 had normal EEG with no history. However, improvements were still observed in these 9 patients. Thus, intrathecal transplantation of autologous BMMNCs along with neurorehabilitation is safe and efficacious in patients with ASD.

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.

Hemorrhagic complications arising from ventricular drainage procedures are typically asymptomatic and of low volume. A particular subset of these complications known as Delayed Intracranial Hemorrhage (DICH) is however recognized for its particularly poor prognosis. We primarily aimed to identify epidemiological characteristics associated with DICH, to shed light on its occurrence and potential risk factors. To do so, we performed a retrospective analysis of a series of ten patients who presented with DICH in the context of a ruptured brain Arteriovenous Malformation (bAVM), and a systematic literature review of all DICH cases reported in the literature. Our ten patients showed delayed neurological deterioration after Ventriculoperitoneal Shunt (VPS) procedure, with a computed tomography (CT) scan revealing a DICH surrounding the ventricular catheter, distinct and away from the nidus of their previously ruptured bAVM. Four patients (40%) rapidly declined and passed away, three (30%) required surgical management and the remaining three (30%) demonstrated gradual clinical improvement with conservative management. In the literature, most patients presenting with DICH had hydrocephalus associated with neurovascular disorders (47% of cases), such as bAVM rupture in our present series. These constatations point out the significance of underlying pathologies potentially predisposing to these unusual complications.

Mood disorders are among the commonest mental disorders worldwide. Epidemiological and clinical evidence suggests that there are close links between infectious diseases and mood disorders, but the strength and direction of these association remain largely unknown. Theoretical models have attempted to explain this link based on evolutionary or immune-related factors, but these have not been empirically verified. The current study examined cross-sectional and longitudinal associations between the incidence of infectious diseases and mood disorders, while correcting for climate and economic factors, based on data from the Global Burden of Disease Studies, 1990-2019. It was found that major depressive disorder was positively associated with lower respiratory infections, while bipolar disorder was positively associated with upper respiratory infections and negatively associated with enteric and tropical infections, both cross-sectionally and over a period of thirty years. These results suggest that a complex, bidirectional relationship exists between these disorders. This relationship may be mediated through the immune system as well as through the gut-brain and lung-brain axes. Understanding the mechanisms that link these groups of disorders could lead to advances in the prevention and treatment of both.

Emotions play a vital role in understanding human behavior and interpersonal relationships. The ability to recognize emotions through Electroencephalogram (EEG) signals offers an alternative to traditional methods, such as questionnaires, enabling the identification of emotional states in a non-intrusive manner. Automatic emotion recognition holds great potential, eliminating the need for clinical examinations or physical visits, thereby contributing significantly to the advancement of Brain-Computer Interface (BCI) technology. However, one of the key challenges lies in effectively selecting and extracting relevant features from the EEG signal to establish meaningful distinctions between different emotional states. The process of feature selection is often time-consuming and demanding. In this research, we propose a groundbreaking approach for automatically identifying three emotional states (positive, negative, and neutral) by leveraging auditory stimulation of EEG signals. Our novel method directly applies the raw EEG signal to a Convolutional Neural Network-Long Short Term Memory (CNN-LSTM) architecture, bypassing the conventional feature extraction and selection steps. This unconventional approach offers a significant departure from existing literature. Our proposed network architecture comprises ten convolutional layers, followed by three LSTM layers and two fully connected layers. Through extensive simulations and evaluations on 12 active channels, our algorithm demonstrates exceptional performance, achieving an accuracy of 97.42\% and 95.23\% for the binary classification of negative and positive emotions, as well as a Cohen's Kappa coefficient of 0.96 and 0.93 for the three-class classification (negative, neutral, and positive), respectively. These promising results highlight the efficacy of our novel methodology and its potential implications in advancing emotion recognition using EEG signals.

Gut microbiota plays a critical role in physiological regulation throughout life and is specifically modified to meet the demands of individual life stages and during pregnancy. Maternal gut microbiota is uniquely adapted to the pregnancy demands of the mother and the developing fetus. Both animal studies in pregnant germ-free rodents and human studies have supported a critical association between the composition of maternal microbiota during pregnancy and fetal development. Gut microbiota may also contribute to the development of the fetal gut-brain axis (GBA), which is increasingly recognized for its critical role in health and disease. Most studies consider birth as the time of GBA activation and focus on postnatal GBA development. This review focuses on GBA development during the prenatal period and the impact of maternal gut microbiota on fetal GBA development. It is hypothesized that adaptation of maternal gut microbiota to pregnancy is critical for the GBA prenatal development and maturation of GBA postnatally. Consequently, factors affecting maternal gut microbiota during pregnancy, such as maternal obesity, diet, stress and depression, infection, and medication, also affect fetal GBA development and are critical for GBA activity postnatally. Altered maternal gut microbiota during gestation has been shown to have long-term impact postnatally and multigenerational effects. Thus, understanding the impact of maternal gut microbiota during pregnancy on fetal GBA development is crucial for managing fetal, neonatal, and adult health, and should be included among public health priorities.

Brain-computer interfaces (BCI) from electroencephalography (EEG) provide a practical approach to support human-technology interaction. In particular, motor imagery (MI) is a widely-used BCI paradigm that guides the mental trial of motor tasks without physical movement. Here, we present a deep learning methodology, named Kernel-based Regularized EEGNet (KREEGNet), leveled on Centered Kernel Alignment and Gaussian Functional Connectivity, explicitly designed for EEG-based MI classification. The approach proactively tackles the challenge of intra-subject variability brought on by noisy EEG records and the lack of spatial interpretability within end-to-end frameworks applied for MI classification. KREEGNet is a refinement of the widely accepted EEGNet architecture, featuring an additional kernel-based layer for regularized Gaussian functional connectivity estimation based on CKA. The superiority of KREEGNet is evidenced by our experimental results from binary and multi-class MI classification databases, outperforming the baseline EEGNet and other state-of-the-art methods. Further exploration of our model’s interpretability is conducted at individual and group levels, utilizing classification performance measures and pruned functional connectivities. Our approach is a suitable alternative for interpretable end-to-end EEG-BCI based on deep learning.

In this study, we developed a model that can predict whether patients with cerebral arteriovenous malformation (AVM) will be cured 36 months after intervention by means of stereotactic radiosurgery (SRS), and identified the most important predictors that explain the probability of being cured. A machine learning (ML) approach was applied using decision tree (DT) and logistic regression (LR) techniques on historical data (sociodemographic, clinical, treatment, angioarchitecture, and radiosurgery procedure) of 202 patients with AVM who underwent SRS at the Instituto de Radiocirugía del Perú (IRP) between 2005 and 2018. The LR model obtained the best results for predicting AVM cure with an accuracy of 92.16%, sensitivity of 92.86%, specificity of 88.89%, precision of 97.50%, and AUC of 97.62%, which shows that ML models are suitable for use for predicting the prognosis of medical conditions such as AVM and can be a support tool for medical decision-making. In addition, several factors were identified that could explain whether patients with AMV would be cured at 36 months with the highest likelihood: the location of the AVM, the occupation of the patient, and the presence of hemorrhage.

To investigate the intricate dynamics of brain activity when interacting with a dynamic environment, it is imperative to continuously generate and update expectations regarding forthcoming events and their corresponding sensory and motor responses. This study aims to explore the interconnectivity in time perception across predictable and unpredictable conditions. The necessary data for this study were acquired from EEG signals, sourced from an existing database that involved an experiment conducted on a group of healthy participants. The individuals were subjected to two distinct conditions, predictable and unpredictable, encompassing various time delays. The functional connectivity between brain regions was estimated using a method known as the phase lag index. This method was employed to discern disparities in time perception between the two conditions. A comprehensive comparison of the two conditions across different delays demonstrated noteworthy variations, particularly in the gamma, beta, and theta frequency bands. The differences between delays were more pronounced in the predictable condition. Subsequently, an in-depth analysis was conducted to scrutinize the dissimilarities between the conditions within each delay. Notably, significant differences were observed across all delays. In the unpredictable condition, an increase in connectivity was detected within the alpha band during the 400-ms delay, specifically between occipital and temporal regions. Moreover, the mean connectivity in the unpredictable condition surpassed that of the predictable condition. In the delta band, distinct connectivity patterns were observed across different delays, involving connections between central and frontal regions. Specifically, a heightened connectivity between central and prefrontal regions was noted during the 83-ms delay. Notably, the right hemisphere of the prefrontal cortex played a vital role in time perception. Furthermore, a decline in connectivity across the delta, theta, and beta bands was observed in both conditions during the longest delay (800 ms) when compared to other delays

Background: This study investigated the incidence, characteristics and functional outcomes associated with unplanned Acute Care Unit Readmissions (ACUR) during inpatient traumatic brain injury (TBI) rehabilitation in an Asian cohort. Methods: Retrospective review of electronic medical records from single rehabilitation unit was conducted from 1 Jan 2012 to 31 Dec 2014. Inclusion criteria were first TBI, aged &gt;18 years, admitted &lt; 6 months of TBI. ACUR were characterized into either of neurological, medical or neurosurgical subtypes. The main outcome measure was discharge Functional Independence Measure (FIM). Secondary outcomes included rehabilitation length of stay (RLOS). Results: Of 121 eligible TBI records, the incidence of ACUR was 14% (n=17), comprising neurologic (76.5%) and medical (23.5%) subtypes, occurring at median of 13 days (IQR 6, 28.5) after rehabilitation admission. Patients without ACUR had significantly higher admission mean (SD) FIM score compared to those with ACUR (FIM ACUR-negative 63.4 (21.1) vs FIM ACUR-positive 50.53(25.4), P =0.026). Significantly lower discharge FIM was noted in those with ACUR compared to those without. (FIM ACUR-positive 65.8(31.4) vs FIM ACUR-negative 85.4 (21.1), P = 0.023) Furthermore, a significant near-doubling of RLOS was noted in ACUR patients compared to non-ACUR counterparts [ACUR-positive median 55 days (IQR 34.50, 87.50) vs ACUR-negative median 28 days (IQR 16.25, 40.00), P = 0.002]. Conclusion: This study highlights the significant negative functional impact and lengthening of rehabilitation duration of ACUR on inpatient rehabilitation outcome for TBI.

Uncontrolled and fast cell proliferation is the cause of brain tumors. Early cancer detection is vitally important in order to save many lives. Brain tumors can be divided into several categories depending on the kind, place of origin, pace of development, and stage of progression; as a result, tumor classification is crucial for targeted therapy. The aim of brain tumor segmentation is to accurately delineate the areas of the brain. A specialist with a thorough understanding of brain illnesses must manually identify the proper type of brain tumor. Additionally, processing a lot of images takes time and is tiresome. Therefore, automatic segmentation and classification techniques are required to speed up and enhance the diagnosis of brain tumors. Tumors can be quickly and safely detected by brain scans using imaging modalities, including computed tomography (CT), magnetic resonance imaging (MRI), and others. Machine learning (ML) and artificial intelligence (AI) have shown promise in the development of algorithms that aid in automatic classification and segmentation utilizing various imaging modalities. This review discussed various types of brain tumors, publicly accessible datasets, enhancement methods, segmentation, feature extraction, classification, machine learning techniques, and deep learning, learning through transfer, for the study of brain tumors.

Neurodegenerative diseases (NDs) affect millions of people worldwide, and to date Alzheimer's and Parkinson's disease are the most common NDs. The risk of developing NDs increases dra-matically with age, and genetic and environmental factors can be crucial in their progression. The main feature of NDs is the abnormal presence of specific proteins that can lead to neuronal death, proteotoxic stress, and alteration of catabolic systems, which are major players in the processes of neurodegeneration and neuroinflammation. Despite research efforts to date, the therapies cur-rently in use for the treatment of NDs provide marginal therapeutic benefit, so the focus is now being direct toward the search of natural products that could be a valuable aid in combating these diseases, including the natural compound Andrographis paniculata (Ap) and especially its main constituent Andrographolide (Andro). Preclinical studies have shown that the aqueous extract of Ap is capable to modulate neuroinflammatory and neurodegenerative responses, determining a reduction in inflammatory markers and oxidative stress in various NDs. Therefore, in this review we will focus on the molecular mechanisms through which Ap and Andro are able to modulate the processes of neurodegeneration and neuroinflammation that are major causes of neuronal death and cognitive decline.

Judo is a popular Japanese martial art and an Olympic sport. Recently, an increasing interest has been observed in the application of judo as a multicomponent exercise, with a growing body of evidence showing that multicomponent exercise improves physical and cognitive performance in older adults. Therefore, this review highlights the benefits of judo training in preventing physical and cognitive decline in older adults. Specifically, first, this review outlines the basic characteristics of judo (philosophy, match, and training). Next, previous studies investigating the effects of judo training on physical and cognitive aspects of older adults are reviewed. Thereafter, the brain mechanisms underlying the effects of judo training in improving physical and cognitive performance are discussed. Throughout this review, judo training demonstrated some positive effects on physical (gait and balance, among others) and cognitive (memory and executive function) function in older adults. These positive effects are attributed to a variety of changes in the brain (e.g., increased neurotrophic factor expression and increased cerebral blood flow, among others), that affect different brain regions and networks both functionally and structurally. From these findings, this review concludes that judo training can be an effective way to maintain and prevent physical and cognitive decline in older adults.

Fisetin has been shown to be beneficial for brain injury and age-related brain disease via different mechanisms. The purpose of this study was to determine the presence of senescent cells and the effects of fisetin on cellular senescence in the brain and other organs in old sheep, a more translational model. Approximately 6-7 years old female sheep (N=6) were treated with 100mg/kg fisetin or vehicle two consecutive days a week for 8 weeks. All organs were harvested at the time of sacrifice. Histology, immunofluorescent staining, as well as Q-PCR was performed on different regions of brain tissues and organs. Our results indicated that Fisetin treatment at the current regimen did not affect general morphology of the brain. The presence of senescent cells in both cerebral brain cortex and cerebellum was detected by SA-β-Gal staining. More senescent cells were observed in the gray matter when compared to the white matter of the cerebral brain cortex. These senescent cells are mainly neurons in both gray and white matter of either cerebral brain cortex or cerebellum. Fisetin treatment showed a trend of decrease SA-β-Gal cells in gray matter of both cerebral brain cortex and cerebellum and significantly decreased in brain cortex white matter. Furthermore, fisetin treatment significantly decreased P16+ cells in brain cortex NEUN+ neurons, GFAP+ astrocytes, IBA+ microglia cells in both gray and white matter of cerebral brain cortex. Fisetin treatment also significantly decreased P16+ cells in microglia cells and a trend of decrease of P16+ cells in astrocytes in the non- (Cornu Ammonis) CA area of hippocampus. However, fisetin treatment did not change P16+ cells in the NEUN+ neurons in the CA1-4 area of the hippocampus. At the mRNA level, fisetin showed a decreased in GLB1 in heart ventricle muscle tissue and spleen tissues but not in other organs tested. Fisetin treatment also showed a decreased antioxidant gene SOD1 and increased CAT in spleen and bone marrow. Fisetin treatment showed variable effects in SASP and inflammasome genes in different organs. In conclusion, we found senescent cells are widely present in the cerebral brain cortex and cerebellum of old sheep. In addition, fisetin treatment decreased senescent cells as well as P16+ cells in the neurons in both gray and white matter of cerebral brain cortex and in astrocytes and microglia cells of cerebral brain cortex and non-CA area of hippocampus. Fisetin treatment represents a promising therapeutic strategy for age-related brain disease.

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.

Aging is a major risk factor for Alzheimer's disease (AD). AD mouse models are frequently used to assess pathology, behavior, and memory in AD research. While the pathological characteristics of AD are well established, our understanding of the changes in the metabolic phenotypes with age and pathology is limited. In this work, we used the Promethion cage systems® to monitor changes in physiological metabolic and behavioral parameters with age and pathology in wild-type and 5xFAD mouse models. Then, we assessed whether these parameters could be altered by treatment with oleocanthal, a phenolic compound with neuroprotective properties. Findings demonstrated metabolic parameters such as body weight, food and water intake, energy expenditure, dehydration, and respiratory exchange rate, and the behavioral parameters of sleep patterns and anxiety-like behavior are altered by age and pathology. However, the effect of pathology on these parameters was significantly greater than normal aging, which could be linked to amyloid-β deposition and blood-brain barrier (BBB) disruption. In addition, and for the first time, our findings suggest an inverse correlation between sleep hours and BBB breakdown. Treatment with oleocanthal improved the assessed parameters and reduced anxiety-like behavior symptoms and sleep disturbances. In conclusion, aging and AD are associated with metabolism and behavior changes, with the changes being greater with the latter, which were rectified by oleocanthal. In addition, our findings suggest that monitoring changes in metabolic and behavioral phenotypes could provide a valuable tool to assess disease severity and treatment efficacy in AD mouse models.

Brain metastasis (BrM), involving the spread of cells from a primary tumor through the blood circulation system to the brain microvasculature, eventually progresses despite multiple treatments and remains a substantial contributor to major mortality in patients with advanced- stage cancer. Molecular signatures and immune cellular components of the tumor microenvironment (TME) are emerging as essential regulators involved in establishing an organ-specific metastasis (colonization) and therapeutic response. A comprehensive understanding of detailed characterization and the immune landscape in context of process of BrM formation will greatly expand the horizon of treatments available to target these deadly diseases. In this review, we provide a comprehensive picture of the complex interactions between tumor cells and immune cellular components participated in the BrM process. Based on this knowledge, we will discuss opportunities and challenges for therapeutic strategies against BrM.

With the increment of the aging population in recent years, neurodegenerative diseases exert a major global disease burden, essentially as a result of the lack of treatments that can stop the disease progression. Alzheimer’s Disease (AD) is an example of a neurodegenerative disease, that affects millions of people globally, with no effective treatment. Natural compounds have emerged as a viable therapy to fill a huge gap in AD management, and in recent years, mostly fuelled by the Covid-19 pandemic, RNA-based therapeutics have become a hot topic in the treatment of several diseases. Treatments of neurodegenerative diseases face significant limitations due to the complex and interconnected pathways that lead to their hallmarks and, also due to the necessity to cross the blood–brain barrier. Nanotechnology has contributed to surpass this bottleneck in the treatment of AD, by promoting safe and enhanced drug delivery to the brain. In particular, exosome-like nanoparticles, a hybrid delivery system combining exosomes and liposomes' advantageous features, are demonstrating great potential in the treatment of central nervous system diseases.