Brain Disorders Research Articles

Boiling Histotripsy in Ex Vivo Human Brain: Proof-of-concept

ObjectiveNon-invasive surgical approaches, including boiling histotripsy (BH), are currently being developed for treatment of brain disorders aiming to avoid craniotomy and exposure of intervening tissues, and, thus, minimize associated complications. This work aimed to demonstrate the feasibility of BH for mechanical fractionation of human brain tissues ex vivo under B-mode guidance, with preliminary measurements of tissue stiffness via shear wave elastography (SWE). MethodsYoung's moduli of N=25 human autopsy brain samples obtained from de-identified patients of 51–91 y.o. (median 77 y.o.) were measured via SWE prior to BH sonication. N = 17 volumetric BH lesions (1–4 layers of 5×5 points with 1-mm step) were produced near brain surface (n = 10), in white matter (n = 3), in thalamus (n = 2) and globus pallidus (n = 2) using 12-element 1.5-MHz sector transducer under B-mode guidance with 10-ms or 2-ms pulses delivered 10 or 15 times per sonication point with 1% duty cycle. Post-treatment, the lesions were evaluated grossly through bisection, histologically with H&E staining, and ultrastructurally via scanning and transmission electron microscopy. ResultsYoung's moduli of autopsy brain samples were lower in older patients (from 32.9±6.6 kPa in 51 y.o. to 10±2 kPa in 91 y.o.) and at higher temperature (6–50% lower at 37°С vs 23°С), and were within the range observed clinically. All tested BH treatments performed near the brain surface (i.e., mostly in grey matter) resulted in formation of well demarcated rectangular lesions with homogenized content and sharp boundaries, with majority of residual fragments below 100 microns. The use of shorter pulses (2 ms vs 10 ms) accelerated the treatment at least threefold, and the highest liquefaction rate was 568 mm3/min. White matter was more resistant to BH vs grey matter: at least 15 pulses of 2-ms duration were required per each sonication point, and liquefaction rate was three times lower. The ability of BH to produce lesions in thalamus and globus pallidus was also confirmed. ConclusionThis work presents the first demonstration of boiling histotripsy proof-of-concept in human brain tissues ex vivo under B-mode guidance with clinically relevant treatment rates.

A survey of detection of Parkinson’s disease using artificial intelligence models with multiple modalities and various data preprocessing techniques

Parkinson’s disease (PD) is a neurodegenerative brain disorder that causes symptoms such as tremors, sleeplessness, behavioral problems, sensory abnormalities, and impaired mobility, according to the World Health Organization (WHO). Artificial intelligence, machine learning (ML), and deep learning (DL) have been used in recent studies (2015–2023) to improve PD diagnosis by categorizing patients and healthy controls based on similar clinical presentations. This study investigates several datasets, modalities, and data preprocessing techniques from the collected data. Issues are also addressed, with suggestions for future PD research involving subgrouping and connection analysis using magnetic resonance imaging (MRI), dopamine transporter scan (DaTscan), and single-photon emission computed tomography (SPECT) data. We have used different models like Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) for detecting PD at an early stage. We have used the Parkinson’s Progression Markers Initiative (PPMI) dataset 3D brain images and archived the 86.67%, 94.02%, accuracy of models, respectively.

Behavioral Assays for Comprehensive Evaluation of Cognitive and Neuropsychiatric Comorbidities of Traumatic Brain Injury and Chronic Neurological Disorders.

Neurological deficits, psychiatric disorders, and cognitive impairments often accompany stroke, brain injury, epilepsy, and many neurological disorders, which present intricate comorbidities that challenge recognition and management. There are many tools and paradigms for evaluating learning, memory, anxiety, and depression-like behaviors in lab animal models of brain disorders. However, there is a significant gap between clinical observations and experimental models, which limit understanding of the complex interplay between chronic brain conditions and their impact on cognitive dysfunction and psychiatric impairments. This article describes an overview of experimental rationale, methods, protocols, and strategies for evaluating sensorimotor, affective and cognitive-associated comorbid behaviors in epilepsy, traumatic brain injury (TBI), stroke, spinal cord injury (SCI), and many other neurological disorders. First, we delve into clinical evidence elucidating the profound impact of comorbidities, e.g., psychiatric disorders and cognitive deficits, in individuals with epilepsy. Then, we discuss diverse approaches to assess these comorbidities in experimental models of brain diseases. Finally, we explore the methodologies for assessing motor function, sensorimotor, behavior, and psychiatric health. We cover strategies and protocols enabling these assays, including implementing behavioral paradigms to assess learning and memory, anxiety, and depression-like behaviors in rodents in health and disease conditions. It is essential to consider a comprehensive battery of tests to investigate various behavioral deficits, considering environment, age, and sex differences relevant to the disease, such as TBI, SCI, epilepsy, stroke, and other complex neurological conditions. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC.

Comparison of single shot and multishot diffusion-weighted imaging in 5-T magnetic resonance imaging for brain disease diagnosis.

Diffusion-weighted imaging (DWI) with single-shot echo-planar imaging (ssEPI) is a valuable tool for detecting acute brain lesions but does suffer from image distortions. Multishot echo-planar imaging (msEPI) is a technique for reducing such distortions. This study aimed to compare the image quality and diagnostic efficacy of ssEPI- and msEPI-DWI at 5.0 T for brain disease detection. This study retrospectively reviewed images of 107 consecutive patients with suspected brain diseases who underwent ssEPI- and msEPI-DWI at 5.0 T at the First Affiliated Hospital of University of Science and Technology of China from August 2023 to September 2023. Two radiologists independently graded image quality and measured the image distortion. Signal-to-noise ratio, contrast-to-noise ratio, and apparent diffusion coefficient (ADC) were calculated and compared between ssEPI- and msEPI-DWI. Image quality scores were compared using the Wilcoxon test and other continuous variables by the paired t-test. The diagnostic accuracy of ADC values in distinguishing lesions from normal-appearing tissues was measured with the area under the curve (AUC). Image quality evaluation and distortion analysis revealed that msEPI-DWI significantly outperformed ssEPI-DWI (two-sided P<0.001). No significant difference was observed in signal-to-noise ratio, contrast-to-noise ratio, or ADC values between msEPI- and ssEPI-DWI (two-sided P≥0.601). The ADC values of msEPI- and ssEPI-DWI showed strong correlations for both lesions (r=0.97) and contralateral normal tissues (r=0.91) (two-sided P<0.001). Compared to those of the contralateral white matter, ADC values of low-grade gliomas (LGGs) were significantly higher [ssEPI-DWI: 1,119.9±273.1 vs. 805.1±73.9; msEPI-DWI: 1,196.2±355.6 vs. 757.3±98.0 (unit: ×10-6 mm2/s)], while the ADC values of acute cerebral infarction (ACI) lesions were significantly lower [ssEPI-DWI: 603.9±273.2 vs. 888.9±212.0; msEPI-DWI: 538.0±281.2 vs. 905.0±188.9 (unit: ×10-6 mm2/s)] (two-sided P≤0.003). The AUCs for detecting LGGs were excellent for both ssEPI-DWI [AUC =0.934; 95% confidence interval (CI): 0.84-1.00] and msEPI-DWI (AUC =0.944; 95% CI: 0.86-1.00) (two-sided P<0.001; two-sided DeLong test: P=0.833). As compared to ssEPI-DWI, msEPI-DWI, when performed at 5.0 T, demonstrated superior image quality and less anatomical distortion in a wide spectrum of brain diseases and showed promising diagnostic performance for LGGs and ACI. In the future, msEPI-DWI at 5.0 T could become clinically routine in the diagnosis and grading of brain disorders.

Diverse phenotype of Ménière’s disease associated with family history, thyroid disorder, migraine and associated disorders

ObjectiveTo better understand the clinical phenotype of Ménière’s disease (MD), we examined family history, thyroid disorder, migraine, and associated disorders in complaints of people living with MD. MethodWe designed the study as a retrospective and examined data gathered from 912 participants with MD. Their data were originally collected by the Finnish Ménière Federation (FMF). The survey data included individual case histories for environmental factors, comorbidities, disease-specific complaints, impact-related questions, cognitive complaints, health-related quality of life (HRQoL), and sense of coherence (SOC). ResultsWe observed significant differences between those with and without sporadic occurrence, family history, thyroid disorder, and migraine-associated complaints. Family history explained 20% of variability in patient complaints. Patients with a family history of MD whose disease started at younger age experienced balance problems, more severe vertigo spells, more severe vestibular drop attacks (VDA), and less nausea, although they had good SOC. Thyroid disorder explained 14% of variability in patient complaints. MD patients with a thyroid disorder comorbidity suffered more often from constant dizziness, balance problems, greater impact of hearing problems, cognitive complaints, and poor HRQoL. Migraine explained 12% of variability in patients’ complaints and was associated with poor SOC and cognitive balance problems. MD patients with both thyroid disorder and migraine used antidepressants more often than other groups. Logistic regression analysis showed comorbidities of ischemic brain disorder (among 7.1%), kidney insufficiency (among 1.2%), and diabetes (among 7.3%) had statistically significant but restricted association with balance and gait problems, VDA, and reduced HRQoL. ConclusionsFamily history of MD and thyroid disorder or migraine comorbidities in MD influence the complaint pattern and partially explain complex symptom profiles, including symptoms of cognitive problems. Confounders play a minimal role in complaint profile and impact of MD whereas comorbidities influence the complaint structure and partly explain the complex symptom profile in MD.

Identifying modifiable factors associated with neuroimaging markers of brain health.

Brain structural alterations begin long before the presentation of brain disorders; therefore, we aimed to systematically investigate a wide range of influencing factors on neuroimaging markers of brain health. Utilizing data from 30,651 participants from the UK Biobank, we explored associations between 218 modifiable factors and neuroimaging markers of brain health. We conducted an exposome-wide association study using the least absolute shrinkage and selection operator (LASSO) technique. Restricted cubic splines (RCS) were further employed to estimate potential nonlinear correlations. Weighted standardized scores for neuroimaging markers were computed based on the estimates for individual factors. Finally, stratum-specific analyses were performed to examine differences in factors affecting brain health at different ages. The identified factors related to neuroimaging markers of brain health fell into six domains, including systematic diseases, lifestyle factors, personality traits, social support, anthropometric indicators, and biochemical markers. The explained variance percentage of neuroimaging markers by weighted standardized scores ranged from 0.5% to 7%. Notably, associations between systematic diseases and neuroimaging markers were stronger in older individuals than in younger ones. This study identified a series of factors related to neuroimaging markers of brain health. Targeting the identified factors might help in formulating effective strategies for maintaining brain health.

Parallel electrophysiological abnormalities due to COVID-19 infection and to Alzheimer's disease and related dementia.

Many coronavirus disease 2019 (COVID-19) positive individuals exhibit abnormal electroencephalographic (EEG) activity reflecting "brain fog" and mild cognitive impairments even months after the acute phase of infection. Resting-state EEG abnormalities include EEG slowing (reduced alpha rhythm; increased slow waves) and epileptiform activity. An expert panel conducted a systematic review to present compelling evidence that cognitive deficits due to COVID-19 and to Alzheimer's disease and related dementia (ADRD) are driven by overlapping pathologies and neurophysiological abnormalities. EEG abnormalities seen in COVID-19 patients resemble those observed in early stages of neurodegenerative diseases, particularly ADRD. It is proposed that similar EEG abnormalities in Long COVID and ADRD are due to parallel neuroinflammation, astrocyte reactivity, hypoxia, and neurovascular injury. These neurophysiological abnormalities underpinning cognitive decline in COVID-19 can be detected by routine EEG exams. Future research will explore the value of EEG monitoring of COVID-19 patients for predicting long-term outcomes and monitoring efficacy of therapeutic interventions. HIGHLIGHTS: Abnormal intrinsic electrophysiological brain activity, such as slowing of EEG, reduced alpha wave, and epileptiform are characteristic findings in COVID-19 patients. EEG abnormalities have the potential as neural biomarkers to identify neurological complications at the early stage of the disease, to assist clinical assessment, and to assess cognitive decline risk in Long COVID patients. Similar slowing of intrinsic brain activity to that of COVID-19 patients is typically seen in patients with mild cognitive impairments, ADRD. Evidence presented supports the idea that cognitive deficits in Long COVID and ADRD are driven by overlapping neurophysiological abnormalities resulting, at least in part, from neuroinflammatory mechanisms and astrocyte reactivity. Identifying common biological mechanisms in Long COVID-19 and ADRD can highlight critical pathologies underlying brain disorders and cognitive decline. It elucidates research questions regarding cognitive EEG and mild cognitive impairment in Long COVID that have not yet been adequately investigated.

Recent Advances in Medicinal Chemistry of Memantine Against Alzheimer's Disease.

Alzheimer's disease (AD) is a chronic progressive, age-related neurodegenerative brain disorder characterized by the irreversible decline of memory and other cognitive functions. It is one of the major health threat of the 21st century, which affects around 60% of the population over the age of 60 years. The problem of this disease is even more major because the existing pharmacotherapies only provide symptomatic relief without addressing the basic factors of the disease. It is characterized by the extracellular deposition of amyloid β (Aβ) to form senile plaques, and the intracellular hyperphosphorylation of tau to form neurofibrillary tangles (NFTs). Due to the complex pathophysiology of this disease, various hypotheseshave been proposed, including the cholinergic, Aβ, tau, oxidative stress, and the metal-ion hypothesis. Among these, the cholinergic and Aβ hypotheses are the primary targets for addressing AD. Therefore, continuous advances have been made in developing potential cholinesterase inhibitors and N-methyl-D-aspartate (NMDA) receptor antagonists to delay disease progression and restore cholinergic neurotransmission. In this review article, we tried to comprehensively summarize the recent advancement in NMDA receptor antagonist (memantine) and their hybrid analogs as potential disease-modifying agents for the treatment of AD. Furthermore, we also depicted the design, rationale, and SAR analysis of the memantine-based hybrids used in the last decade for the treatment of AD.

Abnormal brain entropy dynamics in ADHD

BackgroundBrain entropy (BEN) is a novel measure for irregularity and complexity of brain activities, which has been used to characterize abnormal brain activities in many brain disorders including attention-deficit/hyperactivity disorder (ADHD). While most research assumes BEN is stationary during scan sessions, the brain in resting state is also a highly dynamic system. The BEN dynamics in ADHD has not been explored. MethodsWe used a sliding window approach to derive the dynamical brain entropy (dBEN) from resting-state functional magnetic resonance imaging (rfMRI) dataset that includes 98 ADHD patients and 111 healthy controls (HCs). We identified 3 reoccurring BEN states. We tested whether the BEN dynamics differ between ADHD and HC, and whether they are associated with ADHD symptom severity. ResultsOne BEN states, characterized by low overall BEN and low within-state BEN located in SMN (sensorimotor network) and VN (visual network), its FW (fractional window) and MDT (mean dwell time) were increased in ADHD and positively correlated with ADHD severity; another state characterized by high overall BEN and low within-state BEN located in DMN (default mode network) and ECN (executive control network), its FW and MDT were decreased in ADHD and negatively correlated with ADHD severity. LimitationsThe window length of dBEN analysis can be further optimized to suit more datasets. The co-variation between dBEN and other dynamical brain metrics was not explored. ConclusionOur findings revealed abnormal BEN dynamics in ADHD, providing new insights into clinical diagnosis and neuropathology of ADHD.

Uptake of Mesenchymal Stem Cell-Derived Exosomes in Mouse Brain through Intranasal Delivery.

Exosomes are nanoscale extracellular vesicles that widely participate in intercellular communication. An increasing number of studies have reported on the neuroprotective effects of stem cell-derived exosomes in brain diseases through various delivery methods. However, only a few reports are available on the delivery and uptake of stem cell-derived exosomes in the brains of mice of different ages. PKH-26-labelled mesenchymal stem cell-derived exosomes were collected, and their uptake was investigated in the brains of mice aged 2 weeks, 2 months, and >6 months, 24 hours after intranasal delivery. No exosomes were distributed in the whole brains of 2-week-old mice after 24 hours of intranasal delivery. However, a small number of exosomes were found in the olfactory bulb, cortex, and hippocampus of 2-month-old mice, with no exosomes observed in the cerebellum. In contrast, a large number of exosomes were ingested in all brain regions, including the olfactory bulb, cortex, hippocampus, and cerebellum, of >6-month-old mice. Exosomes can enter the brains of adult mice through intranasal administration, but there are differences in the uptake rate among mice of different ages. These findings provide a theoretical basis for the future clinical administration of exosomes for treating brain disorders.

Linear Monotonic Inter-electrode Associations as Quantitative EEG for Alcoholism Diagnosis

Alcohol use disorders (AUDs) are associated with alterations in EEG patterns that reflect underlying neural dysfunctions, such as impaired cognitive processing, reduced neural connectivity, and disrupted brain rhythms. These EEG alterations can be indicative of several brain disorders, including cognitive deficits, mood disorders, and neurodegenerative diseases, which are often exacerbated by chronic alcohol abuse. Cognitive impairment in alcoholic subjects is caused due to altered functional connectivity between brain regions that can be quantified using statistical measures such as correlation. This paper proposes novel Quantitative EEG (QEEG) features comprising the band-wise absolute value of inter-electrode correlations as a measure of brain functional connectivity to classify alcoholic and non-alcoholic EEG. The EEG signal is first decomposed into five frequency sub-bands. In each sub-band, the absolute value of the linear Pearson product-moment correlation coefficient is computed between time-series EEG recorded by electrode pairs placed over different brain regions. To reduce the dimensionality of the feature vector, an ensemble feature selection approach is adopted, utilizing ANOVA and Chi-square, in conjunction with greedy forward feature selection wrapper algorithm. Four classifiers, namely SVM, KNN, ANN and RF are utilized for the classification. Among them, the SVM classifier achieves the best classification accuracies of 100% on validation with test data and 99.58% on cross-validation with train data, respectively.

Different effects of migraine associated features on headache impact, pain intensity, and psychiatric conditions in patients with migraine

Migraine is a multifactorial brain disorder characterized by recurrent disabling headaches and their associated features. Several studies have suggested that these features are related to headache impact, pain intensity, and psychiatric conditions. However, differences in the relationship between each associated feature and headache impact, pain intensity, or psychiatric conditions remain unclear. This study aimed to assess the impact of migraine-associated features on headache impact, pain intensity, and psychiatric conditions in patients with migraine. In this two-centered study, patients with migraine without aura (MwoA) were enrolled to exclude those without headaches and avoid the influence of medication overuse, which is commonly associated with chronic migraine. We used multiple logistic regression to analyze the headache impact, pain intensity, and psychiatric conditions measured using the Headache Impact Test (HIT-6), Visual Analog Scale (VAS), Generalized Anxiety Disorder 7-item scale (GAD-7), and Patient Health Questionnaire-9 (PHQ-9). Patients’ likelihood of experiencing symptoms such as nausea, vomiting, photophobia, phonophobia, osmophobia, and allodynia were also recorded. A total of 1103 patients with MwoA were enrolled in this study, and 164 patients were excluded from the study because of missing data. Finally, 939 patients with MwoAs were included. On multiple logistic regression analyses, nausea (odd ratios [OR] 1.87, confidence interval [CI]: 1.37–2.54), vomiting (OR 1.57, CI: 1.11–2.23), photophobia (OR 1.67, CI: 1.18–2.35), and allodynia (OR 1.56, CI: 1.06–2.28) were independent positive predictors of higher HIT-6 scores, and nausea (OR 1.72, CI: 1.22–2.43), vomiting (OR 1.84, CI: 1.29–2.63), phonophobia (OR 1.58, CI: 1.10–2.25), photophobia (OR 1.49, CI: 1.07–2.08), and allodynia (OR 1.81, CI: 1.24–2.66) were independent positive predictors of higher VAS score. Nausea (OR 1.49, CI: 1.09–2.02), phonophobia (OR 2.00, CI: 1.42–2.82), and allodynia (OR 1.81, CI: 1.24–2.63) were independent positive predictors of GAD-7 score. Nausea (OR 1.66, CI: 1.21–2.28), phonophobia (OR 1.49, CI: 1.05–2.11), and allodynia (OR 1.68, CI: 1.16–2.45) were independent positive predictors and vomiting (OR 0.54, CI: 0.37–0.78) was an independent negative predictor of PHQ-9 score. Our results suggest that nausea, vomiting, photophobia, phonophobia, and osmophobia have distinct effects on headache impact, pain intensity, and psychiatric conditions. Understanding these differences can aid in the personalized management of patients with MwoA.

Implementasi Range Of Motion (ROM) Pasif Untuk Meningkatkan Mobilitas Fisik Pada Pasien Dengan Stroke Hemoragik Di Rumah Sakit Vita Insani Pematangsiantar

Stroke is a functional brain disorder in the form of death of neurological nerve cells due to disruption of blood flow in one part of the brain. Hemorrhagic stroke is a ruptured blood vessel in the brain which results in intracranial bleeding. The prevalence of stroke cases every year is 13.7 million and around 5.5 million deaths occur due to stroke. One of the nursing problems that arises in cases of hemorrhagic stroke is impaired physical mobility. Efforts that can be made to overcome physical mobility disorders are passive range of motion (ROM). This research design uses the Case Study method. The sampling method used is purposive sampling. The samples taken were 2 respondents, namely patients with hemorrhagic stroke who were hospitalized at Vita Insani Hospital, Pematangsiantar. The results showed that there was an increase in mobility experienced by hemorrhagic stroke patients, a decrease in muscle strength, Mr. U scales (3) to (4) and in Mr. S scales (2) to (3). Passive range of motion (ROM) is effective in cases of hemorrhagic stroke in increasing physical mobility. Nurses are expected to be able to accompany patients to apply passive range of motion (ROM) in an effort to increase physical mobility in hemorrhagic stroke patients.

Alleviation of Autophagic Deficits and Neuroinflammation by Histamine H3 Receptor Antagonist E159 Ameliorates Autism-Related Behaviors in BTBR Mice

Background/Objectives: Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by social interaction difficulties, repetitive behaviors, and immune dysregulation with elevated pro-inflammatory markers. Autophagic deficiency also contributes to social behavior deficits in ASD. Histamine H3 receptor (H3R) antagonism is a potential treatment strategy for brain disorders with features overlapping ASD, such as schizophrenia and Alzheimer’s disease. Methods: This study investigated the effects of sub-chronic systemic treatment with the H3R antagonist E159 on social deficits, repetitive behaviors, neuroinflammation, and autophagic disruption in male BTBR mice. Results: E159 (2.5, 5, and 10 mg/kg, i.p.) improved stereotypic repetitive behavior by reducing self-grooming time and enhancing spontaneous alternation in addition to attenuating social deficits. It also decreased pro-inflammatory cytokines in the cerebellum and hippocampus of treated BTBR mice. In BTBR mice, reduced expression of autophagy-related proteins LC3A/B and Beclin 1 was observed, which was elevated following treatment with E159, attenuating the disruption in autophagy. The co-administration with the H3R agonist MHA (10 mg/kg, i.p.) reversed these effects, highlighting the role of histaminergic neurotransmission in observed behavioral improvements. Conclusions: These preliminary findings suggest the therapeutic potential of H3R antagonists in targeting neuroinflammation and autophagic disruption to improve ASD-like behaviors.

Expression-based selection identifies a microglia-tropic AAV capsid for direct and CSF routes of administration in mice.

Microglia are critical innate immune cells of the brain. In vivo targeting of microglia using gene-delivery systems is crucial for studying brain physiology and developing gene therapies for neurodegenerative diseases and other brain disorders such as NeuroAIDS. Historically, microglia have been extremely resistant to transduction by viral vectors, including adeno-associated virus (AAV) vectors. Recently, there has been some progress demonstrating the feasibility and potential of using AAV to transduce microglia after direct intraparenchymal vector injection. Data suggests that combining specific AAV capsids with microglia-specific gene expression cassettes to reduce neuron off-targeting will be key. However, no groups have developed AAV capsids for microglia transduction after intracerebroventricular (ICV) injection. The ICV route of administration has advantages such as increased brain biodistribution while avoiding issues related to systemic injection. Here, we performed an in vivo selection using an AAV peptide display library that enables recovery of capsids that mediate transgene expression in microglia. Using this approach, we identified a capsid, MC5, which mediated enhanced transduction of microglia after ICV injection compared to AAV9. Furthermore, MC5 enhanced both the efficiency (85%) and specificity (93%) of transduction compared to a recently described evolved AAV9 capsid for microglia targeting after direct injection into the brain parenchyma. Exploration of the use of MC5 in a mouse models of Alzheimer's disease revealed transduced microglia surrounding and within plaques. Overall, our results demonstrate that the MC5 capsid is a useful gene transfer tool to target microglia in vivo by direct and ICV routes of administration.

Neuroprotective Properties of Rutin Hydrate against Scopolamine-Induced Deficits in BDNF/TrkB/ERK/CREB/Bcl2 Pathways.

Background/Objectives: Alzheimer's disease (AD) is an age-related degenerative brain disorder characterized by a progressive decline in cognitive function and memory. This study aimed to evaluate whether rutin hydrate (RH) has neuroprotective effects in an AD-like learning and memory impairment rat model induced by scopolamine (SCO). Methods: The rats were administered with RH (100 mg/kg) and SCO (1.5 mg/kg) and underwent behavioral tests, including the Morris water maze test, Y-maze test, and passive avoidance test, to evaluate their learning and memory abilities. Additionally, long-term potentiation (LTP) was induced to observe changes in the field excitatory postsynaptic potential (fEPSP) activity. Results: RH treatment attenuated the SCO-induced shortening of step-through latency in the passive avoidance (PA) test, increased the percentage of alternation in the Y-maze, and increased the time spent in the target zone in the Morris water maze (MWM). Moreover, RH increased the total activity of fEPSP following theta burst stimulation and attenuated the SCO-induced blockade of fEPSP. RH also ameliorated the SCO-induced decrease in the expression levels of the BDNF, TrkB, ERK, CREB, and Bcl-2 proteins and the increase in the Bax protein level in the rat hippocampus. This demonstrates that RH has beneficial neuroprotective effects in the brain, improving learning, memory, and synaptic plasticity in rats. Conclusions: Our results highlight the molecular and cellular mechanisms through which RH exerts its neuroprotective effects in the prevention and treatment of learning and memory deficit disorders. RH could potentially be used as a therapeutic strategy for the restoration of learning and memory function and the prevention of the progression of AD.

Nine Neuroimaging-AI Endophenotypes Unravel Disease Heterogeneity and Partial Overlap across Four Brain Disorders: A Dimensional Neuroanatomical Representation.

Disease heterogeneity poses a significant challenge for precision diagnostics. Recent work leveraging artificial intelligence has offered promise to dissect this heterogeneity by identifying complex intermediate brain phenotypes, herein called dimensional neuroimaging endophenotypes (DNEs). We advance the argument that these DNEs capture the degree of expression of respective neuroanatomical patterns measured, offering a dimensional neuroanatomical representation for studying disease heterogeneity and similarities of neurologic and neuropsychiatric diseases. We investigate the presence of nine such DNEs derived from independent yet harmonized studies on Alzheimer's disease (AD1-2)1, autism spectrum disorder (ASD1-3)2, late-life depression (LLD1-2)3, and schizophrenia (SCZ1-2)4, in the general population of 39,178 participants in the UK Biobank study. Phenome-wide associations revealed prominent associations between the nine DNEs and phenotypes related to the brain and other human organ systems. This phenotypic landscape aligns with the SNP-phenotype genome-wide associations, revealing 31 genomic loci associated with the nine DNEs (Bonferroni corrected P-value < 5×10-8/9). The DNEs exhibited significant genetic correlations, colocalization, and causal relationships with multiple human organ systems and chronic diseases. A causal effect (odds ratio=1.25 [1.11, 1.40], P-value=8.72×10-4) was established from AD2, characterized by focal medial temporal lobe atrophy, to AD. The nine DNEs, along with their polygenic risk scores, significantly enhanced the predictive accuracy for 14 systemic disease categories, particularly for conditions related to mental health and the central nervous system, as well as mortality outcomes. These findings underscore the potential of the nine DNEs to capture the expression of disease-related brain phenotypes in individuals of the general population and to relate such measures with genetics, lifestyle factors, and chronic diseases. All results are publicly available at https://labs-laboratory.com/medicine/.

Optimizing Brain-Computer Interfaces for Methampetamine Use Disorder through Quantitative Electroencephalography (QEEG) and Transcranial Doppler Analysis: Article Review

A Brain-Computer Interface (BCI) is a system that allows a person to control external devices using only their brain activity. It works by translating brain signals into commands that can be understood by a computer. Several lines of evidence demonstrated the deleterious effect of methamphetamine (MA) on neurological and psychological functions. The use of amphetamines, such as MA, is associated with cerebrovascular complications such as cerebrovascular accidents (CVA) ,hemorrhage, hypoxic damage and vasculitis. Interestingly, while changes to cerebral blood flow (CBF) in response to acute amphetamine exposure have been reported. Transcranial Color Doppler (TCCD) is a non-invasive medical imaging technique that uses ultrasound waves to measure blood flow velocity in the major arteries of the brain, specifically within the circle of Willis. The research paper you referenced explores the use of TCCD as a potential measurement modality for BCIs. Quantitative electroencephalogram (qEEG) is a powerful tool for understanding brain function qEEG can reveal specific brain wave patterns associated with drug addiction, potentially providing insights into the neurobiological mechanisms underlying cravings, withdrawal symptoms, and relapse risk in Methamphetamine User Disorder (MUD). There is growing research interest in using Transcranial dopller as a measurement modality for BCIs.Here are some of the key considerations for using Transcranial doppler in BCIs: Mental Tasks, signal processing and classification, accuracy and reliability. Transcranial doppler provides information about blood flow in specific arteries but lacks detailed spatial information about brain activity. These patterns could vary depending on the type of drug, the severity of addiction, and individual differences. Transcranial doppler in measuring middle cerebral artery (MCA) blood flow velocity parameters (peak systolic velocity (PSV) and mean flow velocity (MFV)). qEEG can help researchers investigate the complex interplay between addiction and other brain disorders, like depression or anxiety. Characteristic qEEG in drugs addiction Increased Theta (4-8 Hz) and delta (1-4 Hz) brain waves are often associated with sleep and relaxation. However, research has shown that individuals with drug addiction may have increased theta and delta activity, particularly in the frontal and temporal regions of the brain. Altered Beta (13-30 Hz) brain waves are generally associated with wakefulness, alertness, and cognitive processing. Studies have observed both increases and decreases in beta activity in individuals with drug addiction, depending on the type of drug, the stage of addiction, and the specific brain regions being examined. The results of this research have important practical implications for building an diagnostic and functional assement with a better understanding of an using technology.

Treatment of neurologic pathology and inflammation in Machado-Joseph disease through in vivo self-assembled siRNA.

Machado-Joseph disease, also known as Spinocerebellar ataxia type 3 (MJD/SCA3), is a fatal autosomal dominant hereditary ataxia characterized by cerebellar ataxia resulting from the abnormal expansion of CAG repeats in exon 10 of the ATXN3 gene. Presently, there is no effective treatment for SCA3. Small interfering RNAs (siRNAs) are emerging as potential therapeutic strategies to specifically target the disease-causing mutant ATXN3 (mATXN3) protein. However, the delivery efficiency of siRNAs remains a major obstacle for clinical application, particularly in brain disorders. This study aimed to develop a synthetic biology strategy to reprogram the host liver as a tissue chassis to induce and deliver in vivo self-assembled siRNAs (IVSA-siRNAs) to target the ATXN3 gene. A synthetic construct directed by a cytomegalovirus promoter was designed to encode a neuron-targeting rabies virus glycoprotein tag and mATXN3-siRNA. After intravenous injection, the synthetic construct was taken up by mouse livers, which were then reprogrammed to enable the self-assembly, production, and secretion of small extracellular vesicles (sEVs) encapsulating mATXN3-siRNA. The sEV-encapsulated mATXN3-siRNA was further transported through the endogenous circulating system of sEVs, crossing the blood-brain barrier and reaching the cerebellar cortex and spinal cerebellar tract, where they silenced the ATXN3 gene. Treatment with the synthetic construct for 8 or 12 weeks led to significant improvements in motor balance ability and reduction of cerebellar atrophy in YACMJD84.2 transgenic mice. The number of Purkinje cells in the cerebellar cortex was significantly increased, and the loss of myelin basic protein was reduced. Moreover, the quantity of neurotoxic nuclear inclusion bodies and the expression of glial fibrillary acidic protein, which promotes neuroinflammation in activated astrocytes, were decreased significantly. The synthetic construct facilitated the generation and delivery of IVSA-siRNA to the cerebellar cortex and spinal cerebellar tract, thereby inhibiting the expression of mATXN3 protein. This treatment successfully addressed motor impairments, alleviated neuropathological phenotypes, and mitigated neuroinflammation in YACMJD84.2 transgenic mice. Our strategy effectively overcomes the primary challenges associated with siRNA therapy for cerebellar ataxia, offering a promising avenue for future clinical treatments.

Network pharmacology and experimental validation reveal the mechanisms of sniffing essential oil of Acori Tatarinowii rhizoma in treating olfactory dysfunction

Ethnopharmacological relevanceAcorus tatarinowii Rhizoma, a traditional Chinese medicine known for open the orifices and transform phlegm, is used in the treatment of brain disorders. The essential oil of Acorus tatarinowii Rhizoma (EOAT) has demonstrated neuroprotective properties clinically. However, research into its effect on Olfactory Dysfunction (OD) remains limited. Aim of the studyThis study aimed to investigate the effects and mechanisms of sniffing EOAT on improving olfactory function in a 3-Methylindole (3-MI)-induced OD mouse model. Materials and methodsThe research involved intraperitoneal injection of 3-MI to induce OD in mice. The effects of EOAT treatment were assessed on olfactory function, olfactory bulb (OB) pathology, inflammatory factors, olfactory marker protein (OMP), microglial activation, and related pathway proteins and mRNA. ResultsBased on the GC-MS analysis results of EOAT and network pharmacology studies, we predicted 18 targets associated with the treatment of OD. SLC6A3, MAOB, DRD1, and PTGS2 were identified as the core targets of EOAT against OD. Molecular docking and KEGG enrichment results indicated that EOAT may exert anti-inflammatory effects by acting on the core target PTGS2, with its anti-inflammatory mechanism possibly related to the PI3K/Akt signaling pathway. Subsequent animal experiments confirmed that inhalation of EOAT significantly increased the body weight of OD model mice, shortened the foraging time, enhanced the expression of OMP in OB, reduced damage to the OB cells, and improved olfactory function. Meanwhile, EOAT significantly alleviated the inflammatory response in OB of OD model mice, inhibited the activation of microglial cells, and suppressed the expression of PI3K/Akt signaling pathway proteins and mRNA. ConclusionEOAT inhalation could improve olfactory function in 3-MI-induced OD model. The underlying mechanism may be related to the modulation of the PI3K/Akt signaling pathway.