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[Display omitted] Brain diseases, mainly including acute brain injuries, neurodegenerative diseases, and mental disorders, have posed a significant threat to human health worldwide. Due to the limited regenerative capability and the existence of the blood–brain barrier, the brain was previously thought to be separated from the rest of the body. Currently, various cross-talks between the central nervous system and peripheral organs have been widely described, including the brain-gut axis, the brain-liver axis, the brain-skeletal muscle axis, and the brain-bone axis. Moreover, several lines of evidence indicate that leveraging systemic biology intervention approaches, including but not limited to lifestyle interventions, exercise, diet, blood administration, and peripheral immune responses, have demonstrated a significant influence on the progress and prognosis of brain diseases. The advancement of innovative proteomic and transcriptomic technologies has enriched our understanding of the nuanced interplay between peripheral organs and brain diseases. An array of novel or previously underappreciated blood-derived factors have been identified to play pivotal roles in mediating these communications. In this review, we provide a comprehensive summary of blood-to-brain communication following brain diseases. Special attention is given to the instrumental role of blood-derived signals, positing them as significant contributors to the complex process of brain diseases. The insights presented here aim to bridge the current knowledge gaps and inspire novel therapeutic strategies for brain diseases. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhejiang University: Science B is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Rationale: Theories of addiction guide scientific progress, funding priorities, and policy development and ultimately shape how people experiencing or recovering from addiction are perceived and treated. Choice theories of addiction are heterogenous, and different models have divergent implications. This breeds confusion among laypeople, scientists, practitioners, and policymakers and reduces the utility of robust findings that have the potential to reduce the global burden of addiction-associated harms. Objective: Here we differentiate classes of choice models and articulate a novel framing for a class of addiction models, called contextual models, which share as a first principle the influence of the environment and other contextual factors on behavior within discrete choice contexts. Results: These models do not assume that all choice behaviors are voluntary, but instead that both proximal and distal characteristics of the choice environment–and particularly the benefits and costs of both drug use and non-drug alternatives–can influence behavior in ways that are outside of the awareness of the individual. From this perspective, addiction is neither the individual's moral failing nor an internal uncontrollable urge but rather is the result of environmental contingencies that reinforce the behavior. Conclusions: Contextual models have implications for guiding research, practice, and policy, including identification of novel target mechanisms while also improving existing interventions. [ABSTRACT FROM AUTHOR]

[Display omitted] Brain disorders represent an ever-increasing health challenge worldwide. While conventional drug therapies are less effective due to the presence of the blood-brain barrier, infusion-based methods of drug delivery to the brain represent a promising option. Since these methods are mechanically controlled and involve multiple physical phases ranging from the neural and molecular scales to the brain scale, highly efficient and precise delivery procedures can significantly benefit from a comprehensive understanding of drug-brain and device-brain interactions. Behind these interactions are principles of biophysics and biomechanics that can be described and captured using mathematical models. Although biomechanics and biophysics have received considerable attention, a comprehensive mechanistic model for modeling infusion-based drug delivery in the brain has yet to be developed. Therefore, this article reviews the state-of-the-art mechanistic studies that can support the development of next-generation models for infusion-based brain drug delivery from the perspective of fluid mechanics, solid mechanics, and mathematical modeling. The supporting techniques and database are also summarized to provide further insights. Finally, the challenges are highlighted and perspectives on future research directions are provided. Despite the immense potential of infusion-based drug delivery methods for bypassing the blood-brain barrier and efficiently delivering drugs to the brain, achieving optimal drug distribution remains a significant challenge. This is primarily due to our limited understanding of the complex interactions between drugs and the brain that are governed by principles of biophysics and biomechanics, and can be described using mathematical models. This article provides a comprehensive review of state-of-the-art mechanistic studies that can help to unravel the mechanism of drug transport in the brain across the scales, which underpins the development of next-generation models for infusion-based brain drug delivery. More broadly, this review will serve as a starting point for developing more effective treatments for brain diseases and mechanistic models that can be used to study other soft tissue and biomaterials. [ABSTRACT FROM AUTHOR]

Brain disease is considered a major cause of increased mortality worldwide. Clinical decision support system (CDSS) is utilized for predicting individuals with brain disease in its earlier state. This work proposes a novel disease prediction approach for earlier prediction by handling the dataset issues, where an improved SMOTE sampling approach is used for balancing the target data distribution. Then, Extreme Convolutional Network Model (XCNM) is used for predicting the disease with better accuracy. For the validation purpose, two publicly available ADNI-1 and ADNI-2 online datasets are used for the model construction, and the outcomes are compared with other techniques like Support Vector Machine (SVM), Artificial Neural Network (ANN), Voxel-based SVM (VW-SVM), standard Convolutional Neural Network (CNN), Deep Neural Network (DNN) and Weighted-Score Multimodal DNN (WS-MTDNN). The outcomes show that the proposed XCNM model outperforms various existing approaches with 94% and 95% accuracies on the input ADNI-1 and ADNI-2 datasets. Also, the CDSS-based framework is designed to assist the doctors in critical cases and help reduce the mortality rate. [ABSTRACT FROM AUTHOR]

Reactive oxygen species (ROS) plays an important role in regulating the physiological function of organisms. However, excessive ROS content may cause oxidative stress and biomolecule destruction, resulting in inflammation, tumors, neurodegenerative diseases and other diseases. Nanozymes with the activities of antioxidant enzymes such as superoxide dismutase or catalase can reduce the content of ROS in tissue, regulate the dynamic balance of redox and reduce the damage of ROS to tissue, and the nanozymes has the advantages of strong stability, adjustable activity and simple synthesis conditions. In this paper, the latest research on nanozymes in the treatment of ROS-related brain diseases are reviewed. [ABSTRACT FROM AUTHOR]

Effective management of cellular components is essential for maintaining brain health, and studies have identified several crucial biological processes in the brain. Among these, autophagy and the role of exosomes in cellular communication are critical for brain health and disease. The interaction between autophagy and exosomes in the nervous system, as well as their contributions to brain damage, have garnered significant attention. This review summarizes that exosomes and their cargoes have been implicated in the autophagy process in the pathophysiology of nervous system diseases. Furthermore, the onset and progression of neurological disorders may be affected by autophagy regulation of the secretion and release of exosomes. These findings may provide new insights into the potential mechanism by which autophagy mediates different exosome secretion and release, as well as the valuable biomedical applications of exosomes in the prevention and treatment of various brain diseases by targeting autophagy.

Treating brain diseases presents significant challenges due to neuronal degeneration, inflammation, and the intricate nature of the brain. Stimuli-responsive hydrogels, designed to closely resemble the brain’s extracellular matrix, have emerged as promising candidates for controlled drug delivery and tissue engineering. These hydrogels have the unique ability to encapsulate therapeutic agents and release them in a controlled manner when triggered by environmental stimuli. This property makes them particularly suitable for delivering drugs precisely to targeted areas of the brain, while minimizing collateral damage to healthy tissue. Their preclinical success in treating various brain diseases in animal studies underscores their translational potential for human brain disease treatment. However, a deeper understanding of their long-term behavior, biodistribution, and biocompatibility within the brain remains crucial. Furthermore, exploring novel hydrogel systems and therapeutic combinations is paramount for advancing towards more effective treatments. This review summarizes the latest advancements in this field over the past 5 years, specifically highlighting preclinical progress with novel stimuli-responsive hydrogels for treating brain diseases.

As brain diseases can severely affect society, studies on the diagnosis of brain diseases are gaining importance. China is focused on counteracting the issues in brain disease diagnosis and treatment. Magnetic resonance imaging (MRI) has the advantages of high resolution and noninvasive nature, making it a preferred technique for brain disease research and clinical examination, providing rich databases for brain disease diagnosis. Deep learning is used in various fields due to its scalability and flexibility, and it has shown great potential for further development. Owing to recent developments in deep learning, it has made impressive achievements in various fields, such as computer vision and natural language processing, exhibiting great potential for its development and impact on brain disease diagnosis. Deep learning is being increasingly used for the diagnosis of brain disorders. We categorized studies reporting the use of deep learning for brain disease diagnosis by the type of disease to provide insights into the latest developments in this field. We cover the following aspects in this review. First, we reviewed and summarized the application of deep learning in the diagnosis of three typical brain disorders: autism spectrum disorder (ASD), schizophrenia (SZ), and Alzheimer’s disease (AD). Second, we reviewed commonly used datasets and available open-source tools for diagnosing these three brain disorders. Finally, we summarized and predicted the application of deep learning in the diagnosis of brain disorders. The review focused on the diagnosis of the aforementioned brain disorders. ASD is a neurodevelopmental disorder that occurs in early childhood. SZ is a psychiatric disorder that occurs in young adulthood. AD is a brain disorder that commonly occurs in old age. We illustrated the application of deep learning in the diagnosis of these brain disorders based on the characteristics of their different inputs. While using MRI as an input source, most convolutional neural networks were used as backbone networks to design feature extraction methods. However, while working with data containing sequence information from many time points, recurrent neural networks were used to extract key information from the sequences. Apart from directly processing images as input, many studies extracted manual features, constructed graphs of manual features, and used graph neural networks for analysis. This approach yielded remarkable results. Moreover, our findings indicated that graph neural network–based analysis methods are being commonly used to diagnose brain disorders.

Abstract Abnormal inflammatory states in the brain are associated with a variety of brain diseases. The dynamic changes in the number and function of immune cells in cerebrospinal fluid (CSF) are advantageous for the early prediction and diagnosis of immune diseases affecting the brain. The aggregated factors and cells in inflamed CSF may represent candidate targets for therapy. The physiological barriers in the brain, such as the blood‒brain barrier (BBB), establish a stable environment for the distribution of resident immune cells. However, the underlying mechanism by which peripheral immune cells migrate into the brain and their role in maintaining immune homeostasis in CSF are still unclear. To advance our understanding of the causal link between brain diseases and immune cell status, we investigated the characteristics of immune cell changes in CSF and the molecular mechanisms involved in common brain diseases. Furthermore, we summarized the diagnostic and treatment methods for brain diseases in which immune cells and related cytokines in CSF are used as targets. Further investigations of the new immune cell subtypes and their contributions to the development of brain diseases are needed to improve diagnostic specificity and therapy.

Currently, there is a lack of effective medicines capable of halting or reversing the progression of neurodegenerative disorders, including amyotrophic lateral sclerosis, Parkinson’s disease, multiple sclerosis, or Alzheimer’s disease. Given the unmet medical need, it is necessary to reevaluate the existing paradigms of how to target these diseases. When considering neurodegenerative diseases from a systemic neurometabolic perspective, it becomes possible to explain the shared pathological features. This innovative approach presented in this paper draws upon extensive research conducted by the authors and researchers worldwide. In this review, we highlight the importance of metabolic mitochondrial dysfunction in the context of neurodegenerative diseases. We provide an overview of the risk factors associated with developing neurodegenerative disorders, including genetic, epigenetic, and environmental factors. Additionally, we examine pathological mechanisms implicated in these diseases such as oxidative stress, accumulation of misfolded proteins, inflammation, demyelination, death of neurons, insulin resistance, dysbiosis, and neurotransmitter disturbances. Finally, we outline a proposal for the restoration of mitochondrial metabolism, a crucial aspect that may hold the key to facilitating curative therapeutic interventions for neurodegenerative disorders in forthcoming advancements.

Abstract Gene delivery to, and expression in, the mouse brain is important for understanding gene functions in brain development and disease, or testing gene therapies. Here, we describe an approach to express a transgene in the mouse brain in a cell-type-specific manner. We use stereotaxic injection of a transgene-expressing adeno-associated virus into the mouse brain via the intracerebroventricular route. We demonstrate stable and sustained expression of the transgene in neurons of adult mouse brain, using a reporter gene driven by a neuron-specific promoter. This approach represents a rapid, simple, and cost-effective method for global gene expression in the mouse brain, in a cell-type-specific manner, without major surgical interventions. The described method represents a helpful resource for genetically engineering mice to express a therapeutic gene, for gene therapy studies, or to deliver genetic material for genome editing and developing knockout animal models.

Abnormal inflammatory states in the brain are associated with a variety of brain diseases. The dynamic changes in the number and function of immune cells in cerebrospinal fluid (CSF) are advantageous for the early prediction and diagnosis of immune diseases affecting the brain. The aggregated factors and cells in inflamed CSF may represent candidate targets for therapy. The physiological barriers in the brain, such as the blood‒brain barrier (BBB), establish a stable environment for the distribution of resident immune cells. However, the underlying mechanism by which peripheral immune cells migrate into the brain and their role in maintaining immune homeostasis in CSF are still unclear. To advance our understanding of the causal link between brain diseases and immune cell status, we investigated the characteristics of immune cell changes in CSF and the molecular mechanisms involved in common brain diseases. Furthermore, we summarized the diagnostic and treatment methods for brain diseases in which immune cells and related cytokines in CSF are used as targets. Further investigations of the new immune cell subtypes and their contributions to the development of brain diseases are needed to improve diagnostic specificity and therapy. [ABSTRACT FROM AUTHOR]

Cerebral strokes, the abrupt cessation of blood flow to the brain, lead to a cascade of events, resulting in cellular damage due to oxygen and nutrient deprivation. Contemporary lifestyle factors, including high glucose levels, heart disease, obesity, and diabetes, heighten the risk of stroke. This research investigates the application of robust machine learning (ML) algorithms, including logistic regression (LR), random forest (RF), and K-nearest neighbor (KNN), to the prediction of cerebral strokes. Stroke data is collected from Harvard Dataverse Repository. The data includes—clinical, physiological, behavioral, demographic, and historical data. The Synthetic Minority Oversampling Technique (SMOTE), adaptive synthetic sampling (ADASYN), and the Random Oversampling Technique (ROSE) are used to address class imbalances to improve the accuracy of minority classes. To address the challenge of forecasting strokes from partial and imbalanced physiological data, this study introduces a novel hybrid ML approach by combining a machine learning method with an oversampling technique called ADASYN_RF. ADASYN is an oversampling technique used to resample the imbalanced dataset then RF is implemented on the resampled dataset. Also, other oversampling techniques and ML models are implemented to compare the results. Notably, the RF algorithm paired with ADASYN achieves an exceptional performance of 99% detection accuracy, exhibiting its dominance in stroke prediction. The proposed approach enables cost-effective, precise stroke prediction, providing a valuable tool for clinical diagnosis. [ABSTRACT FROM AUTHOR]

Hypoxia plays a significant role in the development of various cerebral diseases, many of which are associated with the potential risk of recurrence due to mitochondrial damage. Conventional drug treatments are not always effective for hypoxia-related brain diseases, necessitating the exploration of alternative compounds. In this study, we investigated the potential of diphenyl diselenide [(PhSe)2] to ameliorate locomotor impairments and mitigate brain mitochondrial dysfunction in zebrafish subjected to hypoxia. Additionally, we explored whether these improvements could confer resistance to recurrent hypoxia. Through a screening process, an appropriate dose of (PhSe)2 was determined, and animals exposed to hypoxia received a single intraperitoneal injection of 100 mg/kg of the compound or vehicle. After 1 h from the injection, evaluations were conducted on locomotor deficits, (PhSe)2 content, mitochondrial electron transport system, and mitochondrial viability in the brain. The animals were subsequently exposed to recurrent hypoxia to assess the latency time to hypoxia symptoms. The findings revealed that (PhSe)2 effectively crossed the blood–brain barrier, attenuated locomotor deficits induced by hypoxia, and improved brain mitochondrial respiration by modulating complex III. Furthermore, it enhanced mitochondrial viability in the telencephalon, contributing to greater resistance to recurrent hypoxia. These results demonstrate the beneficial effects of (PhSe)2 on both hypoxia and recurrent hypoxia, with cerebral mitochondria being a critical target of its action. Considering the involvement of brain hypoxia in numerous pathologies, (PhSe)2 should be further tested to determine its effectiveness as a potential treatment for hypoxia-related brain diseases. [ABSTRACT FROM AUTHOR]

Gene delivery to, and expression in, the mouse brain is important for understanding gene functions in brain development and disease, or testing gene therapies. Here, we describe an approach to express a transgene in the mouse brain in a cell-type-specific manner. We use stereotaxic injection of a transgene-expressing adeno-associated virus into the mouse brain via the intracerebroventricular route. We demonstrate stable and sustained expression of the transgene in neurons of adult mouse brain, using a reporter gene driven by a neuron-specific promoter. This approach represents a rapid, simple, and cost-effective method for global gene expression in the mouse brain, in a cell-type-specific manner, without major surgical interventions. The described method represents a helpful resource for genetically engineering mice to express a therapeutic gene, for gene therapy studies, or to deliver genetic material for genome editing and developing knockout animal models. [ABSTRACT FROM AUTHOR]

Copyright of Acta Neurológica Colombiana is the property of Colombian Association of Neurology / Asociacion Colombiana de Neurologia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This document is a compilation of various scientific articles and studies on the use of transcranial photobiomodulation (PBM) for the treatment of brain diseases. The articles cover a range of topics, including the effects of PBM on different brain diseases such as Parkinson's disease, traumatic brain injury, depression, and Alzheimer's disease. The studies suggest that PBM has potential therapeutic effects, improving cognitive function, reducing inflammation, and promoting cell survival in the brain. However, further research is needed to fully understand the mechanisms and optimize the parameters of PBM treatment. [Extracted from the article]

Precise imaging is essential for the accurate diagnosis and surgical guidance of brain diseases but it is challenging due to the difficulties in crossing the blood-brain barrier (BBB), the difficulties in disease lesion targeting, and the limited contrast in the brain environment. Nano-imaging agents were characterized by functionalized modifications, high contrast, small size, and high biocompatibility, thus providing advantages in BBB crossing, brain targeting, imaging resolution, and real-time monitoring, holding great potential in brain disease imaging. Specific characteristics in brain environment and brain diseases (e.g., marker proteins on the BBB, the pathogenic proteins in the neurodegenerative diseases or brain tumors, and the tumor and inflammatory microenvironment) provide opportunities for the functionalized nano-imaging agents to improve BBB crossing and disease targeting. Moreover, the versatile nano-imaging agents are endowed with therapeutic agents to facilitate the theranostics of brain diseases. Here, we summarized the common materials and imaging techniques of nano-imaging agents and their imaging treatment applications. We discussed their BBB penetration, environmental response for disease targeting, and therapeutic effects. We also provided insights on the advantages, challenges, and application of nano-imaging agents in detecting and treating brain diseases such as neurodegenerative diseases, brain tumors, stroke, and traumatic brain injury. These discussions will help develop nano-imaging agents-based theranostic platforms for the precise diagnosis and treatment of brain diseases. [ABSTRACT FROM AUTHOR]

Abstract Acupuncture has been widely used in stroke and post-stroke rehabilitation (PSR), but there is no literature on the bibliometric analysis of acupuncture for stroke. This study aimed to characterize the global publications and analyze the trends of acupuncture for stroke in the past 40 years. We identified 1157 publications from the Web of Science Core Collection. The number of publications grew slowly in the first three decades from 1980 until it started to grow after 2010, with significant growth in 2011–2012 and 2019–2020. China, the USA, and South Korea are the top three countries in this field, and China has formed good internal cooperative relations. Early studies focused on the clinical efficacy of acupuncture for stroke. In the last five years, more emphasis has been placed on the effectiveness of acupuncture in treating sequelae and complications, combined with neuroimaging studies to explore the mechanisms of brain injury repair and neurological recovery. Acupuncture for stroke has a vast research potential, and researchers from different countries/regions and organizations still need to remove academic barriers to enhance communication and collaboration.

Precision nutrition and nutrigenomics are emerging in the development of therapies for multiple diseases. The ketogenic diet (KD) is the most widely used clinical diet, providing high fat, low carbohydrate, and adequate protein. KD produces ketones and alters the metabolism of patients. Growing evidence suggests that KD has therapeutic effects in a wide range of neuronal diseases including epilepsy, neurodegeneration, cancer, and metabolic disorders. Although KD is considered to be a low-side-effect diet treatment, its therapeutic mechanism has not yet been fully elucidated. Also, its induced keto-response among different populations has not been elucidated. Understanding the ketone metabolism in health and disease is critical for the development of KD-associated therapeutics and synergistic therapy under any physiological background. Here, we review the current advances and known heterogeneity of the KD response and discuss the prospects for KD therapy from a precision nutrition perspective.

Brain health means optimal physiological brain function across the normal life-course. It encompasses not only healthy brain aging but also brain diseases, their diagnosis and treatment. In all these areas, molecular science has advanced our understanding.This multi-disciplinary review combines viewpoints from laboratory science, clinical medicine and the bioscience industry. First, we review the advances that molecular science has brought to brain health in the past twenty years. These include therapeutic antibodies for CNS diseases (multiple sclerosis, Alzheimer disease) and the dramatic introduction of RNA-targeted therapeutics. Second, we highlight areas where greater molecular understanding is needed. Salient examples are the relation of brain structure to cognitive symptoms, and molecular biomarkers for diagnosis, target discovery and testing of interventions. Finally, we speculate on aspects of molecular science that are likely to advance brain health in the next twenty years. These include: cell senescence and chronobiology; gene editing (notably, CRISPR) and RNA targeting (RNA interference, miRNA manipulation); brain-immune interactions; novel drug targets (AQP4, HIF1, Toll-like receptors); and novel chemistry to make new drugs (molecular machines, quantum molecular modelling and “click” chemistry). Early testing of the relationships between molecular pathways and clinical manifestations will drive much-needed breakthroughs in neurology and psychiatry.

Acupuncture has been widely used in stroke and post-stroke rehabilitation (PSR), but there is no literature on the bibliometric analysis of acupuncture for stroke. This study aimed to characterize the global publications and analyze the trends of acupuncture for stroke in the past 40 years. We identified 1157 publications from the Web of Science Core Collection. The number of publications grew slowly in the first three decades from 1980 until it started to grow after 2010, with significant growth in 2011–2012 and 2019–2020. China, the USA, and South Korea are the top three countries in this field, and China has formed good internal cooperative relations. Early studies focused on the clinical efficacy of acupuncture for stroke. In the last five years, more emphasis has been placed on the effectiveness of acupuncture in treating sequelae and complications, combined with neuroimaging studies to explore the mechanisms of brain injury repair and neurological recovery. Acupuncture for stroke has a vast research potential, and researchers from different countries/regions and organizations still need to remove academic barriers to enhance communication and collaboration. Highlights: For the first time, we analyzed hotspots related to the field of acupuncture for stroke research using a bibliometric approach, focusing on the most critical indicators, including researchers, countries, research institutions, and journals. 1157 publications from 60 countries/regions contributed to this research theme. China is the main producer of acupuncture for stroke and has formed a cooperation cluster. It is worth noting that researchers from different countries/regions and organizations still need to remove academic barriers to enhance communication and collaboration. Future research trends are focused on providing high-quality clinical evidence, integrating neurological disciplines, exploring new models with multidisciplinary overlap, and exploring the development of artificially intelligent acupuncture robots. The integration of acupuncture with neuroscience and computational science, as well as deep learning and artificial intelligence, are hotspots in acupuncture for stroke. [ABSTRACT FROM AUTHOR]

Seizures are caused by increased neuronal firing activity resulting from reduced inhibitory effect and enhancement of inhibitory modulation to suppress this activity is used as a therapeutic tool. However, recent experiments have shown a counterintuitive phenomenon that inhibitory modulation does not suppress but elicit post-inhibitory rebound (PIR) spike along with seizure to challenge the therapeutic tool. The nonlinear mechanism to avoid the PIR spike can present theoretical guidance to seizure treatment. This paper focuses on identifying credible bifurcations that underlie PIR spike by modulating multiple parameters in multiple theoretical models. The study identifies a codimension-2 bifurcation called saddle--node homoclinic orbit (SNHOB), which is an intersection between saddle node bifurcation on invariant cycle (SNIC) and other two bifurcations. PIR spike cannot be evoked for the SNIC far from the SNHOB but induced for the SNIC close to the SNHOB, which extends the bifurcation condition for PIR spike from the well-known Hopf to SNIC. Especially, in a thalamic neuron model, increases of conductance of T-type Ca2+ (T Ca) channel induce SNIC bifurcation approaching to the SNHOB to elicit PIR spikes, closely matching experimental results of the absence seizure or Parkinson diseases. Such results imply that, when inhibition is employed to relieve absence seizure and Parkinson diseases related to PIR spike, modulating SNIC to get far from the SNHOB to avoid PIR spike is the principle. The study also addresses the complex roles of T Ca current and comprehensive relationships between PIR spike and nonlinear conceptions such as bifurcation types and shapes of threshold curve. [ABSTRACT FROM AUTHOR]

Mitochondria play a vital role in maintaining cellular energy homeostasis, regulating apoptosis, and controlling redox signaling. Dysfunction of mitochondria has been implicated in the pathogenesis of various brain diseases, including neurodegenerative disorders, stroke, and psychiatric illnesses. This review paper provides a comprehensive overview of the intricate relationship between mitochondria and brain disease, focusing on the underlying pathological mechanisms and exploring potential therapeutic opportunities. The review covers key topics such as mitochondrial DNA mutations, impaired oxidative phosphorylation, mitochondrial dynamics, calcium dysregulation, and reactive oxygen species generation in the context of brain disease. Additionally, it discusses emerging strategies targeting mitochondrial dysfunction, including mitochondrial protective agents, metabolic modulators, and gene therapy approaches. By critically analysing the existing literature and recent advancements, this review aims to enhance our understanding of the multifaceted role of mitochondria in brain disease and shed light on novel therapeutic interventions. [ABSTRACT FROM AUTHOR]

Abstract Background Malignant hyperthermia is an extremely dangerous condition that can occur with exposure to volatile inhalant anesthetics and depolarizing muscle relaxants, and that requires immediate intervention. Neurological complications have rarely been reported, with no reports of electroencephalographic abnormalities or encephalopathy. Here, we report a case of severe electroencephalographic abnormality in the acute phase of malignant hyperthermia that eventually led to diffuse cerebral cortical damage. Case presentation A 15-month-old Japanese boy underwent a Rastelli procedure to correct a double-outlet right ventricle and pulmonary atresia. Sevoflurane was used for induction and maintenance of anesthesia during surgery. After withdrawal from the heart–lung machine, his body temperature rose at a rate of 0.1 ℃/minute, and when he left the operating room, his core body temperature had reached 42 ℃. After admission to the intensive care unit, tachycardia, high PaCO2, and progressive metabolic acidosis were observed. A clinical grading scale score of 63 indicated malignant hyperthermia, and dantrolene was administered. The pupils were dilated, and the electroencephalogram showed persistent generalized continuous multifocal spikes. Midazolam, levetiracetam, and fosphenytoin were administered without improvement, and thiamylal and ketamine were infused continuously. After the electroencephalogram shifted to burst suppression, the epileptic firing gradually decreased, and the background electroencephalogram became lower in amplitude. Magnetic resonance imaging of the head performed after the patient was hemodynamically stable suggested diffuse cerebral cortical damage. Severe mental retardation, hypertonia, and quadriplegia were observed as neurological complications. Conclusions In this case, despite the use of high-dose anticonvulsants, the patient showed severe electroencephalogram abnormality, resulting in diffuse cortical damage. Hyperthermia is known to damage the central nervous system by causing increased brain pressure and cerebral edema, which may have triggered the severe neuronal excitation that we observed in this case. The presence of systemic inflammatory response syndrome and the patient’s background, including young age and ethnicity, might also have been factors. Malignant hyperthermia can be complicated by encephalopathy, and continuous electroencephalogram monitoring should be considered.

Antibody therapeutics are limited in treating brain diseases due to poor blood-brain barrier (BBB) penetration. We have discovered that poly 2-methacryloyloxyethyl phosphorylcholine (PMPC), a biocompatible polymer, effectively facilitates BBB penetration via receptor-mediated transcytosis and have developed a PMPC-shell-based platform for brain delivery of therapeutic antibodies, termed nanocapsule. Yet, the platform results in functional loss of antibodies due to epitope masking by the PMPC polymer network, which necessitates the incorporation of a targeting moiety and degradable crosslinker to enable on-site antibody release. In this study, we developed a novel platform based on site-oriented conjugation of PMPC to the antibody, allowing it to maintain key functionalities of the original antibody. With an optimized PMPC chain length, the PMPC-antibody conjugate exhibited enhanced brain delivery while retaining epitope recognition, cellular internalization, and antibody-dependent cellular phagocytic activity. This simple formula incorporates only the antibody and PMPC without requiring additional components, thereby addressing the issues of the nanocapsule platform and paving the way for PMPC-based brain delivery strategies for antibodies.

Brain diseases is a wide range of disorders and diseases that affect the brain. They can change a person's behavior, personality, and capacity for thought and function. CT images are more essential than conventional clinical tests for detecting brain hemorrhage accurately. MRI images of the brain can reveal even small abnormalities in the cranial region, helping providers diagnose a wide variety of conditions, ranging from brain stroke, cancers, aneurysms, and Alzheimer's. This paper proposes a novel Fused dual neural (FDN) network for detecting brain cancer, stroke, aneurysms, and Alzheimer using Brain Medical Images (BMI) the combination of MRI and CT. In BMI, the adaptive bilateral filter reduces noise artifacts. Google Net is used to extract features from pre-processed MRI images, and Mobile Net is used to extract features from pre-processed CT images. The integration of extracted features from Google Net and Mobile Net is fused by the Wrapper method. Finally, the Deep Belief Network is employed for classifying brain stroke, cancer, Aneurysm, and Alzheimer's diseases using BMI images. The quantitative analysis of the suggested method is determined using the parameters like specificity, recall, precision, F1 score, and accuracy. The proposed FDN achieves a high classification accuracy rate of 98.19%, 97.68%, 94.31%, and 93.82% for detecting stroke, cancer, Aneurysm, and Alzheimer respectively. The proposed FDN model improves the overall accuracy by 5.35%, 3.14%, 9.48%, 5.33%, and 0.55% better than Faster R-CNN, CNN, Inception-V3, DCNN, and Fine-tuning Network respectively. [ABSTRACT FROM AUTHOR]

An automated diagnosis system is crucial for helping radiologists identify brain abnormalities efficiently. The convolutional neural network (CNN) algorithm of deep learning has the advantage of automated feature extraction beneficial for an automated diagnosis system. However, several challenges in the CNN-based classifiers of medical images, such as a lack of labeled data and class imbalance problems, can significantly hinder the performance. Meanwhile, the expertise of multiple clinicians may be required to achieve accurate diagnoses, which can be reflected in the use of multiple algorithms. In this paper, we present Deep-Stacked CNN, a deep heterogeneous model based on stacked generalization to harness the advantages of different CNN-based classifiers. The model aims to improve robustness in the task of multi-class brain disease classification when we have no opportunity to train single CNNs on sufficient data. We propose two levels of learning processes to obtain the desired model. At the first level, different pre-trained CNNs fine-tuned via transfer learning will be selected as the base classifiers through several procedures. Each base classifier has a unique expert-like character, which provides diversity to the diagnosis outcomes. At the second level, the base classifiers are stacked together through neural network, representing the meta-learner that best combines their outputs and generates the final prediction. The proposed Deep-Stacked CNN obtained an accuracy of 99.14% when evaluated on the untouched dataset. This model shows its superiority over existing methods in the same domain. It also requires fewer parameters and computations while maintaining outstanding performance. [ABSTRACT FROM AUTHOR]

In recent years, brain diseases have seriously threatened human health due to their high morbidity and mortality. Achieving efficient drug delivery to provide satisfactory therapeutic outcomes is currently the greatest challenge in treating brain diseases. The main challenges are the structural peculiarities of the brain and the inability to transport drugs across the blood–brain barrier. Biomimetic nanodelivery systems (BNDSs) applied to the brain have been extensively developed in the preclinical phase to surmount these challenges. Considering the inherent properties of BNDSs, the substantially enhanced ability of BNDS to carry therapeutic agents and their higher selectivity toward lesions offer new opportunities for developing safe and effective therapies. This review summarizes brain-targeting nanotherapies, particularly advanced therapies with biomimetic nano-assistance. Prospects for developing BNDSs and the challenges of their clinical translation are discussed. Understanding and implementing biomimetic nanotherapies may facilitate the development of new targeted strategies for brain disorders. Using different bionanomaterials to treat brain disorders. Use of different bionanomaterials for the treatment of brain diseases, e.g., cell membranes, exosomes, viral vectors, and receptor-mediated biomimetic approaches [Display omitted] • Advanced biomimetic nano-delivery systems for the treatment of brain diseases have been illustrated. • Highlighted pathological mechanisms of BBB in different brain diseases and biomimetic strategies to cope with it. • The perspectives and challenges for accelerating the clinical translation of biomimetic nano-delivery systems are highlighted. [ABSTRACT FROM AUTHOR]

Background: Malignant hyperthermia is an extremely dangerous condition that can occur with exposure to volatile inhalant anesthetics and depolarizing muscle relaxants, and that requires immediate intervention. Neurological complications have rarely been reported, with no reports of electroencephalographic abnormalities or encephalopathy. Here, we report a case of severe electroencephalographic abnormality in the acute phase of malignant hyperthermia that eventually led to diffuse cerebral cortical damage. Case presentation: A 15-month-old Japanese boy underwent a Rastelli procedure to correct a double-outlet right ventricle and pulmonary atresia. Sevoflurane was used for induction and maintenance of anesthesia during surgery. After withdrawal from the heart–lung machine, his body temperature rose at a rate of 0.1 ℃/minute, and when he left the operating room, his core body temperature had reached 42 ℃. After admission to the intensive care unit, tachycardia, high PaCO2, and progressive metabolic acidosis were observed. A clinical grading scale score of 63 indicated malignant hyperthermia, and dantrolene was administered. The pupils were dilated, and the electroencephalogram showed persistent generalized continuous multifocal spikes. Midazolam, levetiracetam, and fosphenytoin were administered without improvement, and thiamylal and ketamine were infused continuously. After the electroencephalogram shifted to burst suppression, the epileptic firing gradually decreased, and the background electroencephalogram became lower in amplitude. Magnetic resonance imaging of the head performed after the patient was hemodynamically stable suggested diffuse cerebral cortical damage. Severe mental retardation, hypertonia, and quadriplegia were observed as neurological complications. Conclusions: In this case, despite the use of high-dose anticonvulsants, the patient showed severe electroencephalogram abnormality, resulting in diffuse cortical damage. Hyperthermia is known to damage the central nervous system by causing increased brain pressure and cerebral edema, which may have triggered the severe neuronal excitation that we observed in this case. The presence of systemic inflammatory response syndrome and the patient's background, including young age and ethnicity, might also have been factors. Malignant hyperthermia can be complicated by encephalopathy, and continuous electroencephalogram monitoring should be considered. [ABSTRACT FROM AUTHOR]

Brain channelopathies are a group of neurological disorders that result from genetic mutations affecting ion channels in the brain. Ion channels are specialized proteins that play a crucial role in the electrical activity of nerve cells by controlling the flow of ions such as sodium, potassium, and calcium. When these channels are not functioning properly, they can cause a wide range of neurological symptoms such as seizures, movement disorders, and cognitive impairment. In this context, the axon initial segment (AIS) is the site of action potential initiation in most neurons. This region is characterized by a high density of voltage-gated sodium channels (VGSCs), which are responsible for the rapid depolarization that occurs when the neuron is stimulated. The AIS is also enriched in other ion channels, such as potassium channels, that play a role in shaping the action potential waveform and determining the firing frequency of the neuron. In addition to ion channels, the AIS contains a complex cytoskeletal structure that helps to anchor the channels in place and regulate their function. Therefore, alterations in this complex structure of ion channels, scaffold proteins, and specialized cytoskeleton may also cause brain channelopathies not necessarily associated with ion channel mutations. This review will focus on how the AISs structure, plasticity, and composition alterations may generate changes in action potentials and neuronal dysfunction leading to brain diseases. AIS function alterations may be the consequence of voltage-gated ion channel mutations, but also may be due to ligand-activated channels and receptors and AIS structural and membrane proteins that support the function of voltage-gated ion channels. [ABSTRACT FROM AUTHOR]

Enhancers are cis-acting elements that control the transcription of target genes and are transcribed into a class of noncoding RNAs (ncRNAs) termed enhancer RNAs (eRNAs). eRNAs have shorter half-lives than mRNAs and long noncoding RNAs; however, the frequency of transcription of eRNAs is close to that of mRNAs. eRNA expression is associated with a high level of histone mark H3K27ac and a low level of H3K27me3. Although eRNAs only account for a small proportion of ncRNAs, their functions are important. eRNAs can not only increase enhancer activity by promoting the formation of enhancer-promoter loops but also regulate transcriptional activation. Increasing numbers of studies have found that eRNAs play an important role in the occurrence and development of brain diseases; however, further research into eRNAs is required. This review discusses the concept, characteristics, classification, function, and potential roles of eRNAs in brain diseases. [ABSTRACT FROM AUTHOR]

Explicitly or implicitly, psychopathology is often defined in terms of statistical deviance, requiring that an affected individual be sufficiently distant from the norm in some dimension of psychological or neural function. In recent decades, the dominant paradigm in psychiatric research has focused primarily on deviance in neural function, treating psychopathology as disease of the brain. We argue that these conceptualizations are misguided. We recently proposed a novel theory of psychopathology, based in cybernetics and drawing additionally from neuroscience, psychometrics, and personality theory (DeYoung & Krueger, 2018a). In this theory, deviations from the norm in psychological and neural functioning serve as important risk factors for psychopathology but are not in themselves necessary or sufficient to identify psychopathology, which requires the presence of cybernetic dysfunction. Psychopathology is defined as persistent failure to move toward one's goals, due to failure to generate effective new goals, interpretations, or strategies when existing ones prove unsuccessful. We argue that adopting a cybernetic theory to replace conceptualizations of psychopathology as statistical deviance or brain disease would facilitate improvements in measurement, diagnosis, prevention, and treatment of psychopathology. General Scientific Summary: In our new theory of psychopathology, to be considered, mentally ill people must be persistently unable to move toward their important life goals, due to failure to generate effective new goals, interpretations, or strategies when existing ones prove unsuccessful. This theory invalidates the typical assumptions that psychopathology is necessarily a function of having unusual characteristics and that mental illness is really disease of the brain. [ABSTRACT FROM AUTHOR]

Abstract Glioma is the most common malignant tumors in the brain. Previous studies have revealed that, as the innate immune cells in nervous system, microglia cells were involved in glioma pathology. And, the resident microglia displayed its specific biological roles which distinguished with peripheral macrophages. In this study, an integrated analysis was performed based on public resource database to explore specific biological of microglia within glioma. Through comprehensive analysis, the biological characterization underlying two conditions, glioma microglia compared to glioma macrophage (MicT/MacT) as well as glioma microglia compared to normal microglia (MicT/MicN), were revealed. Notably, nine core MicT/MicN genes displayed closely associations with glioma recurrence and prognosis, such as P2RY2, which was analyzed in more than 2800 glioma samples from 25 studies. Furthermore, we applied a random walk based strategy to identify microglia specific subpathways and developed SubP28 signature for glioma prognostic analysis. Multiple validation data sets confirmed the predictive performance of SubP28 and involvement in molecular subtypes. The associations between SuP28 score and microglia M1/M2 polarization were also explored for both GBM and LGG types. Finally, a comprehensive drug-subpathway network was established for screening candidate medicable molecules (drugs) and identifying therapeutic subpathway targets. In conclusions, the comprehensive analysis of microglia related gene and functional signatures in glioma pathobiologic events by large-scale data sets displayed a framework to dissect inner connection between microglia and glioma, and identify robust signature for glioma clinical implications.