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Dopamine, the main catecholamine neurotransmitter plays an important role in renal, cardiovascular, central nervous systems, and pathophysiological processes. The abnormal dopamine levels can result in neurological disorders such as Parkinson's, Alzheimer's, schizophrenia, acute anxiety, neuroblastoma and also contribute to cognitive dysfunctions. Given the widespread importance of dopamine concentration levels, it is imperative to develop sensors that are able to monitor dopamine. Herein, we have developed pre-anodized disposable paper electrode modified with 1-pyrenebutyric acid, for the selective and sensitive determination of dopamine. The sensor was characterized with Fourier transform infrared spectroscopy, Energy dispersive X-ray spectroscopy, X-ray photoelectron spectroscopy, and electrochemical techniques for addressing the robust formation and electrochemical activity. The modified electrode exhibited excellent electrocatalytic activity towards dopamine without the common interference from ascorbic acid. The calibration plot for the dopamine sensor resulted linear range from 0.003 μM to 0.5 μM with a detection limit of 0.11 nM. The sensor's potential utility was tested by monitoring dopamine concentration changes in rat brain homogenates when subjected to neurotoxicity. The developed sensor was validated with gold-standard UV-Vis spectroscopy studies and computational studies were performed to understand the interaction between 1-pyrenebutyric acid and dopamine., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Type 2 diabetes mellitus has a worldwide prevalence of 10.5% in the adult population (20-79 years), and by 2045, the prevalence is expected to keep rising to one in eight adults living with diabetes. Mild cognitive impairment has a global prevalence of 19.7% in adults aged 50 years. Both conditions have shown a concerning increase in prevalence rates over the past 10 years, highlighting a growing public health challenge. Future forecasts indicate that the prevalence of dementia (no estimations done for individuals with mild cognitive impairment) is expected to nearly triple by 2050. Type 2 diabetes mellitus is a risk factor for the development of cognitive impairment, and such impairment increase the likelihood of poor glycemic/metabolic control. High phytate intake has been shown to be a protective factor against the development of cognitive impairment in observational studies. Diary phytate intake might reduce the micro- and macrovascular complications of patients with type 2 diabetes mellitus through different mechanisms. We describe the protocol of the first trial (the PHYND trial) that evaluate the effect of daily phytate supplementation over 56 weeks with a two-arm double-blind placebo-controlled study on the progression of mild cognitive impairment, cerebral iron deposition, and retinal involvement in patients with type 2 diabetes mellitus. Our hypothesis proposes that phytate, by inhibiting advanced glycation end product formation and chelating transition metals, will improve cognitive function and attenuate the progression from Mild Cognitive Impairment to dementia in individuals with type 2 diabetes mellitus and mild cognitive impairment. Additionally, we predict that phytate will reduce iron accumulation in the central nervous system, mitigate neurodegenerative changes in both the central nervous system and retina, and induce alterations in biochemical markers associated with neurodegeneration., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Pujol, Sanchis, Tamayo, Nicolau, Grases, Espino, Estremera, Rigo, Amengual, Rodríguez, Ribes, Gomila, Simó-Servat and Masmiquel.)

Decision prediction based on neurophysiological signals is of great application value in many real-life situations, especially in human-AI collaboration or counteraction. Single-trial analysis of electroencephalogram (EEG) signals is a very valuable step in the development of an online decision-prediction system. However, previous EEG-based decision-prediction methods focused mainly on averaged EEG signals of all decision-making trials to predict an individual's general decision tendency (e.g., risk seeking or aversion) over a period rather than on a specific decision response in a single trial. In the present study, we used a rock-paper-scissors game, which is a common multichoice decision-making task, to explore how to predict participants' single-trial choice with EEG signals. Forty participants, comprising 20 females and 20 males, played the game with a computer player for 330 trials. Considering that the decision-making process of this game involves multiple brain regions and neural networks, we proposed a new algorithm named common spatial pattern-attractor metagene (CSP-AM) to extract CSP features from different frequency bands of EEG signals that occurred during decision making. The results showed that a multilayer perceptron classifier achieved an accuracy significantly exceeding the chance level among 88.57% (31 of 35) of participants, verifying the classification ability of CSP features in multichoice decision-making prediction. We believe that the CSP-AM algorithm could be used in the development of proactive AI systems., (© 2023 The Authors. PsyCh Journal published by Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.)

Background: In previous decades, large-scale research has been carried out on bacterial meningitis. In every field, citation analysis is the most significant contribution. The study's objective was to identify and analyze the 100 articles on bacterial meningitis that received the most citations between 2000 and 2023, highlighting the most significant developments in the field. Objective: The objective of this study was to find out what makes a highly influential article by identifying and analyzing the characteristics of the 100 articles in the field of bacterial meningitis that receive the most citations. The goal of this study was to find and examine the 100 articles on bacterial meningitis that received the most citations. Methodology: We identified the top 100 most-cited papers in the field of bacterial meningitis from 55 journals using the Dimensions AI database. The results of each author's analysis of 100 articles were then compared. We gathered fundamental data such as the journal's title, country of publication, and study type. Descriptive counts or percentages were used to compare the various categories. Results: Between the year 2000 and the year 2023, articles were published. The total number of citations ranged from 115 to 1176, with 42 papers receiving more than 200 citations. In 2008, 14 articles were published, followed by 10 in 2000 and 2007. One thousand one hundred and seventy-six times were given to the most-cited paper, whereas 115 times were given to the least-cited article. "Clinical Features and Prognostic Factors in Adults with Bacterial Meningitis," by Diederik van de Beek, et al. (2004) was the article that received the most citations. 1176 people have cited this article. van de Beek Diederik of the Academic Medical Center in The Netherlands is the author who has written the most articles, was mentioned in 14 of the top 100 articles. Papers were primarily published in Pediatrics (n = 9) publication with 1861 citations. The Netherlands came in second with 18 publications, followed by the United States (n = 46). Conclusion: Our study uses bibliometrics and visualization analysis of the most important articles in this field to show the current state of research in the area of bacterial meningitis, provide a history of research trends, and offer a perspective for future bacterial predicts the growth of meningitis. [ABSTRACT FROM AUTHOR]

Introduction and purpose: Impaired cognitive function is a growing public health problem, where dementia is affecting about 47 million people worldwide, and that number is expected to triple by 2050. The MIND (Mediterranean-DASH Intervention for Neurodegenerative Delay) diet is intended to overcome this problem. This article aims to raise awareness of the MIND diet, highlighting how dietary choices can promote cognitive health and delay disease progression. Brief description of the state of knowledge: The MIND diet focuses on foods that support cognitive health and may mitigate these degenerative processes. It emphasizes green leafy vegetables, berries, nuts, olive oil, whole grains, fish, and poultry while limiting red meat, dairy, sweets, and fried foods. These products contain several components with multidirectional neuroprotective effects. Material and method: This work was based on material found on Google Scholar. Articles were selected based on citation counts, publication dates, and relevance, ensuring a comprehensive review of recent findings on the MIND diet's impact on cognitive health. Summary: The MIND diet enhances brain health by incorporating nutrient-dense foods that reduce inflammation, combat oxidative stress, and support neuronal function. Green leafy vegetables, berries, nuts, whole grains, and healthy fats work together to improve cognitive function, support synaptic plasticity, and protect brain structure, leading to slower cognitive decline and a lower risk of neurodegenerative diseases.

A core assumption in the current neurosemantic research is that meanings of concrete words (object nouns, action verbs) are at least partially grounded in modality-specific representations implemented by perceptual and motor cortices. Nevertheless, increasing evidence from the multisensory research suggests that extensive portions of what are traditionally considered modality-specific cortices are in fact supramodal in nature – that is, they can process specific information in multiple sensory modalities and in both normal and sensory-deprived individuals. My central argument in this paper is that the amount of data collected within the supramodal paradigm, although certainly not conclusive, is already robust enough to foster reflections about the role of modality-specificity in the semantic brain and to prompt considerations about the possibility of promoting a property-specific and modality-invariant turn in neurosemantics. [ABSTRACT FROM AUTHOR]

Deep learning (DL) requires a large amount of training data to improve performance and prevent overfitting. To overcome these difficulties, we need to increase the size of the training dataset. This can be done by augmentation on a small dataset. The augmentation approaches must enhance the model's performance during the learning period. There are several types of transformations that can be applied to medical images. These transformations can be applied to the entire dataset or to a subset of the data, depending on the desired outcome. In this study, we categorize data augmentation methods into four groups: Absent augmentation, where no modifications are made; basic augmentation, which includes brightness and contrast adjustments; intermediate augmentation, encompassing a wider array of transformations like rotation, flipping, and shifting in addition to brightness and contrast adjustments; and advanced augmentation, where all transformation layers are employed. We plan to conduct a comprehensive analysis to determine which group performs best when applied to brain CT images. This evaluation aims to identify the augmentation group that produces the most favorable results in terms of improving model accuracy, minimizing diagnostic errors, and ensuring the robustness of the model in the context of brain CT image analysis., (© 2024. International Federation for Medical and Biological Engineering.)

Purpose: To develop neural network (NN)-based quantitative MRI parameter estimators with minimal bias and a variance close to the Cramér-Rao bound., Theory and Methods: We generalize the mean squared error loss to control the bias and variance of the NN's estimates, which involves averaging over multiple noise realizations of the same measurements during training. Bias and variance properties of the resulting NNs are studied for two neuroimaging applications., Results: In simulations, the proposed strategy reduces the estimates' bias throughout parameter space and achieves a variance close to the Cramér-Rao bound. In vivo, we observe good concordance between parameter maps estimated with the proposed NNs and traditional estimators, such as nonlinear least-squares fitting, while state-of-the-art NNs show larger deviations., Conclusion: The proposed NNs have greatly reduced bias compared to those trained using the mean squared error and offer significantly improved computational efficiency over traditional estimators with comparable or better accuracy., (© 2024 International Society for Magnetic Resonance in Medicine.)

As a widely used mental task for functional near-infrared spectroscopy (fNIRS), the original color-word Stroop task has the advantage of being difficult to habituate, but also the disadvantage of being difficult to understand, especially for children. While the introduction of derived Stroop tasks offers highly promising countermeasures, changes in brain activity during these tests have not been well tested. We investigated the degree of habituation between the original and a derived Stroop task by measuring brain activity to obtain a better fNIRS task design. Fourteen healthy adults participated in the study, and a 10-channel fNIRS device was used. A picture-word Stroop task with lower linguistic conflict than the original was conducted. The original and derived Stroop tests were repeated four times in a 1-week interval. We found that the original Stroop test did not show any significant changes in brain activity with repeated measures; however, brain activity decreased during the derived test. The differences in habituation between the original and derived tests may be due to the differences in the strength of the linguistic conflict. Our findings also highlight the need to consider the effects of habituation when using derived Stroop tasks in repeated measures., (© 2024. The Author(s) under exclusive licence to Biomedical Engineering Society.)

Purpose: To explore efficient encoding schemes for quantitative magnetization transfer (qMT) imaging with few constraints on model parameters., Theory and Methods: We combine two recently proposed models in a Bloch-McConnell equation: the dynamics of the free spin pool are confined to the hybrid state, and the dynamics of the semi-solid spin pool are described by the generalized Bloch model. We numerically optimize the flip angles and durations of a train of radio frequency pulses to enhance the encoding of three qMT parameters while accounting for all eight parameters of the two-pool model. We sparsely sample each time frame along this spin dynamics with a three-dimensional radial koosh-ball trajectory, reconstruct the data with subspace modeling, and fit the qMT model with a neural network for computational efficiency., Results: We extracted qMT parameter maps of the whole brain with an effective resolution of 1.24 mm from a 12.6-min scan. In lesions of multiple sclerosis subjects, we observe a decreased size of the semi-solid spin pool and longer relaxation times, consistent with previous reports., Conclusion: The encoding power of the hybrid state, combined with regularized image reconstruction, and the accuracy of the generalized Bloch model provide an excellent basis for efficient quantitative magnetization transfer imaging with few constraints on model parameters., (© 2023 International Society for Magnetic Resonance in Medicine.)

Early diagnosis is crucial to slowing the progression of Alzheimer's disease (AD), so it is urgent to find an effective diagnostic method for AD. This study intended to investigate whether the transfer learning approach of deep Q-network (DQN) could effectively distinguish AD patients using local metrics of resting-state functional magnetic resonance imaging (rs-fMRI) as features. This study included 1310 subjects from the Consortium for Reliability and Reproducibility (CoRR) and 50 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) GO/2. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF) and percent amplitude of fluctuation (PerAF) were extracted as features using the Power 264 atlas. Based on gender bias in AD, we searched for transferable similar parts between the CoRR feature matrix and the ADNI feature matrix, resulting in the CoRR similar feature matrix served as the source domain and the ADNI similar feature matrix served as the target domain. A DQN classifier was pre-trained in the source domain and transferred to the target domain. Finally, the transferred DQN classifier was used to classify AD and healthy controls (HC). A permutation test was performed. The DQN transfer learning achieved a classification accuracy of 86.66% (p < 0.01), recall of 83.33% and precision of 83.33%. The findings suggested that the transfer learning approach using DQN could be an effective way to distinguish AD from HC. It also revealed the potential value of local brain activity in AD clinical diagnosis., (© 2024 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Purpose: To introduce an unsupervised deep-learning method for fast and effective correction of susceptibility artifacts in reversed phase-encode (PE) image pairs acquired with echo planar imaging (EPI)., Methods: Recent learning-based correction approaches in EPI estimate a displacement field, unwarp the reversed-PE image pair with the estimated field, and average the unwarped pair to yield a corrected image. Unsupervised learning in these unwarping-based methods is commonly attained via a similarity constraint between the unwarped images in reversed-PE directions, neglecting consistency to the acquired EPI images. This work introduces a novel unsupervised deep Forward-Distortion Network (FD-Net) that predicts both the susceptibility-induced displacement field and the underlying anatomically correct image. Unlike previous methods, FD-Net enforces the forward-distortions of the correct image in both PE directions to be consistent with the acquired reversed-PE image pair. FD-Net further leverages a multiresolution architecture to maintain high local and global performance., Results: FD-Net performs competitively with a gold-standard reference method (TOPUP) in image quality, while enabling a leap in computational efficiency. Furthermore, FD-Net outperforms recent unwarping-based methods for unsupervised correction in terms of both image and field quality., Conclusion: The unsupervised FD-Net method introduces a deep forward-distortion approach to enable fast, high-fidelity correction of susceptibility artifacts in EPI by maintaining consistency to measured data. Therefore, it holds great promise for improving the anatomical accuracy of EPI imaging., (© 2023 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Inhibition of glycogen phosphorylase (Pyg) - a regulatory enzyme of glycogen phosphorolysis - influences memory formation in rodents. We have previously shown that 2-week intraperitoneal administration of a Pyg inhibitor BAY U6751 stimulated the "rejuvenation" of the hippocampal proteome and dendritic spines morphology and improved cognitive skills of old mice. Given the tedious nature of daily intraperitoneal drug administration, in this study we investigated whether a single dose of BAY U6751 could induce enduring behavioral effects. Obtained results support the efficacy of such treatment in significantly improving the cognitive performance of 20-22-month-old mice. Metabolomic analysis of alterations observed in the hippocampus, cerebellum, and cortex reveal that the inhibition of glycogen phosphorolysis impacts not only glucose metabolism but also various other metabolic processes., (© 2024. The Author(s).)

Microstates represent brief periods of quasi-stable electroencephalography (EEG) scalp topography, offering insights into dynamic fluctuations in event-related potential (ERP) topographies. Despite this, there is a lack of a comprehensive systematic overview of microstate findings concerning cognitive face processing. This review aims to summarize ERP findings on face processing using microstate analyses and assess their effectiveness in characterizing face-related neural representations. A literature search was conducted for microstate ERP studies involving healthy individuals and psychiatric populations, utilizing PubMed, Google Scholar, Web of Science, PsychInfo, and Scopus databases. Twenty-two studies were identified, primarily focusing on healthy individuals (n = 16), with a smaller subset examining psychiatric populations (n = 6). The evidence reviewed in this study suggests that various microstates are consistently associated with distinct ERP stages involved in face processing, encompassing the processing of basic visual facial features to more complex functions such as analytical processing, facial recognition, and semantic representations. Furthermore, these studies shed light on atypical attentional neural mechanisms in Autism Spectrum Disorder (ASD), facial recognition deficits among emotional dysregulation disorders, and encoding and semantic dysfunctions in Post-Traumatic Stress Disorder (PTSD). In conclusion, this review underscores the practical utility of ERP microstate analyses in investigating face processing. Methodologies have evolved towards greater automation and data-driven approaches over time. Future research should aim to forecast clinical outcomes and conduct validation studies to directly demonstrate the efficacy of such analyses in inverse space., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Extensive evidence shows the beneficial effect of adhering to a regular physical activity (PA) pattern on brain health. However, whether the 'weekend warrior' pattern, characterized by concentrated moderate-to-vigorous PA (MVPA) over 1-2 days, is associated with brain health is unclear. Here, we perform a prospective cohort study including 75,629 participants from the UK Biobank with validated accelerometry data. Individuals were classified into three PA patterns using current guideline thresholds: inactive (<150 min week -1 of MVPA), weekend warrior (≥150 min week -1 with ≥50% of total MVPA occurring within 1-2 days) and regularly active (≥150 min week -1 but not meeting weekend warrior criteria). We find that the weekend warrior pattern is associated with similarly lower risks of dementia, stroke, Parkinson's disease, depressive disorders and anxiety compared to a regularly active pattern. Our findings highlight the weekend warrior pattern as a potential alternative in preventive intervention strategies, particularly for those unable to maintain daily activity routines., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: Juvenile myoclonic epilepsy (JME) is characterized by altered patterns of brain functional connectivity (FC). However, the nature and extent of alterations in the spatiotemporal characteristics of dynamic FC in JME patients remain elusive. Dynamic networks effectively encapsulate temporal variations in brain imaging data, offering insights into brain network abnormalities and contributing to our understanding of the seizure mechanisms and origins., Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) data were procured from 37 JME patients and 37 healthy counterparts. Forty-seven network nodes were identified by group-independent component analysis (ICA) to construct the dynamic network. Ultimately, patients' and controls' spatiotemporal characteristics, encompassing temporal clustering and variability, were contrasted at the whole-brain, large-scale network, and regional levels., Results: Our findings reveal a marked reduction in temporal clustering and an elevation in temporal variability in JME patients at the whole-brain echelon. Perturbations were notably pronounced in the default mode network (DMN) and visual network (VN) at the large-scale level. Nodes exhibiting anomalous were predominantly situated within the DMN and VN. Additionally, there was a significant correlation between the severity of JME symptoms and the temporal clustering of the VN., Conclusions: Our findings suggest that excessive temporal changes in brain FC may affect the temporal structure of dynamic brain networks, leading to disturbances in brain function in patients with JME. The DMN and VN play an important role in the dynamics of brain networks in patients, and their abnormal spatiotemporal properties may underlie abnormal brain function in patients with JME in the early stages of the disease., (© 2024. Fondazione Società Italiana di Neurologia.)

Traumatic brain injury is a major cause of morbidity in civilian as well as military populations. Computational simulations of injurious events are an important tool to understanding the biomechanics of brain injury and evaluating injury criteria and safety measures. However, these computational models are highly dependent on the material parameters used to represent the brain tissue. Reported material properties of tissue from the cerebrum and cerebellum remain poorly defined at high rates and with respect to anisotropy. In this work, brain tissue from the cerebrum and cerebellum of male Göttingen minipigs was tested in one of three directions relative to axon fibers in oscillatory simple shear over a large range of strain rates from 0.025 to 250 s -1 . Brain tissue showed significant direction dependence in both regions, each with a single preferred loading direction. The tissue also showed strong rate dependence over the full range of rates considered. Transversely isotropic hyper-viscoelastic constitutive models were fit to experimental data using dynamic inverse finite element models to account for wave propagation observed at high strain rates. The fit constitutive models predicted the response in all directions well at rates below 100 s -1 , after which they adequately predicted the initial two loading cycles, with the exception of the 250 s -1 rate, where models performed poorly. These constitutive models can be readily implemented in finite element packages and are suitable for simulation of both conventional and blast injury in porcine, especially Göttingen minipig, models., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Toll-like receptor 2 (TLR2) belongs to the TLR protein family that plays an important role in the immune and inflammation response system. While TLR2 is predominantly expressed in immune cells, its expression has also been detected in the brain, specifically in microglia and astrocytes. Recent studies indicate that genomic deletion of TLR2 can result in impaired neurobehavioural function. It is currently not clear if the genomic deletion of TLR2 leads to any alterations in the microstructural features of the brain. In the current study, we noninvasively assess microstructural changes in the brain of TLR2-deficient (tlr2 -/- ) zebrafish using state-of-the art magnetic resonance imaging (MRI) methods at ultrahigh magnetic field strength (17.6 T). A significant increase in cortical thickness and an overall trend towards increased brain volumes were observed in young tlr2 -/- zebrafish. An elevated T 2 relaxation time and significantly reduced apparent diffusion coefficient (ADC) unveil brain-wide microstructural alterations, potentially indicative of cytotoxic oedema and astrogliosis in the tlr2 -/- zebrafish. Multicomponent analysis of the ADC diffusivity signal by the phasor approach shows an increase in the slow ADC component associated with restricted diffusion. Diffusion tensor imaging and diffusion kurtosis imaging analysis revealed diminished diffusivity and enhanced kurtosis in various white matter tracks in tlr2 -/- compared with control zebrafish, identifying the microstructural underpinnings associated with compromised white matter integrity and axonal degeneration. Taken together, our findings demonstrate that the genomic deletion of TLR2 results in severe alterations to the microstructural features of the zebrafish brain. This study also highlights the potential of ultrahigh field diffusion MRI techniques in discerning exceptionally fine microstructural details within the small zebrafish brain, offering potential for investigating microstructural changes in zebrafish models of various brain diseases., (© 2024 The Author(s). NMR in Biomedicine published by John Wiley & Sons Ltd.)

Purpose: To investigate whether parallel imaging-imposed geometric coil constraints can be relaxed when using a deep learning (DL)-based image reconstruction method as opposed to a traditional non-DL method., Theory and Methods: Traditional and DL-based MR image reconstruction approaches operate in fundamentally different ways: Traditional methods solve a system of equations derived from the image data whereas DL methods use data/target pairs to learn a generalizable reconstruction model. Two sets of head coil profiles were evaluated: (1) 8-channel and (2) 32-channel geometries. A DL model was compared to conjugate gradient SENSE (CG-SENSE) and L1-wavelet compressed sensing (CS) through quantitative metrics and visual assessment as coil overlap was increased., Results: Results were generally consistent between experiments. As coil overlap increased, there was a significant (p < 0.001) decrease in performance in most cases for all methods. The decrease was most pronounced for CG-SENSE, and the DL models significantly outperformed (p < 0.001) their non-DL counterparts in all scenarios. CS showed improved robustness to coil overlap and signal-to-noise ratio (SNR) versus CG-SENSE, but had quantitatively and visually poorer reconstructions characterized by blurriness as compared to DL. DL showed virtually no change in performance across SNR and very small changes across coil overlap., Conclusion: The DL image reconstruction method produced images that were robust to coil overlap and of higher quality than CG-SENSE and CS. This suggests that geometric coil design constraints can be relaxed when using DL reconstruction methods., (© 2024 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Background: Brain anomalies (BAs) have been the focus of research, as they have a high impact on fetal health but therapeutic and diagnostic approaches are limited., Objectives: In this study, the application and efficiency of exome sequencing (ES) in detecting different cases of BAs in fetuses were evaluated and compared with chromosomal microarray analysis (CMA)., Search Strategy: To conduct this study, three databases including PubMed, Web of Science and Embase were utilised with the keywords 'prenatal', 'diagnoses', 'brain anomalies' and 'exome sequencing'., Selection Criteria: Studies were included based on the STARD checklist, for which the ES and CMA diagnostic yields were calculated., Data Collection and Analysis: Meta-analysis was performed on the included studies using a random-effects model and subgroup analysis to define the risk difference between them., Main Results: We included 11 studies representing 779 fetuses that implemented ES along with imaging techniques. The pooled ES diagnostic yield in fetuses with BAs detected through magnetic resonance imaging (MRI) and ultrasonography was 26.53%, compared with 3.46% for CMA. The risk difference between ES and CMA for complex BAs was 0.36 [95% confidence interval (CI) 0.24-0.47], which was higher than for single BAs (0.22; 95% CI 0.18-0.25]., Conclusions: ES is a useful method with a significantly higher diagnostic yield than CMA for genetic assessment of fetuses with complex BAs detected by imaging techniques. Moreover, ES could be applied to suspected fetuses with related family histories to predict congenital diseases with high efficiency., (© 2023 John Wiley & Sons Ltd.)

Purpose: Widening the availability of fetal MRI with fully automatic real-time planning of radiological brain planes on 0.55T MRI., Methods: Deep learning-based detection of key brain landmarks on a whole-uterus echo planar imaging scan enables the subsequent fully automatic planning of the radiological single-shot Turbo Spin Echo acquisitions. The landmark detection pipeline was trained on over 120 datasets from varying field strength, echo times, and resolutions and quantitatively evaluated. The entire automatic planning solution was tested prospectively in nine fetal subjects between 20 and 37 weeks. A comprehensive evaluation of all steps, the distance between manual and automatic landmarks, the planning quality, and the resulting image quality was conducted., Results: Prospective automatic planning was performed in real-time without latency in all subjects. The landmark detection accuracy was 4.2 ± $$ \pm $$ 2.6 mm for the fetal eyes and 6.5 ± $$ \pm $$ 3.2 for the cerebellum, planning quality was 2.4/3 (compared to 2.6/3 for manual planning) and diagnostic image quality was 2.2 compared to 2.1 for manual planning., Conclusions: Real-time automatic planning of all three key fetal brain planes was successfully achieved and will pave the way toward simplifying the acquisition of fetal MRI thereby widening the availability of this modality in nonspecialist centers., (© 2024 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

The phenomenon of near death and dying experiences has been both of popular interest and of scientific speculation. However, the reality of mental perception at the point of death is currently a subjective experience and has not been formally evaluated. While postmortem gene expression, even in humans, has been evaluated, restoration of postmortem brain activity has heretofore only been attempted in animal models, at the molecular and cellular levels. Meanwhile, progress has been made to translate brain activity of living humans into speech and images. This paper proposes two inter-related thought experiments. First, assuming progress and refinement of the technology of translating human brain activity into interpretable speech and images, can an objective analysis of death experiences be obtained by utilizing these technologies on dying humans? Second, can human brain function be revived postmortem and, if so, can the relevant technologies be utilized for communication with (recently) deceased individuals? In this paper, these questions are considered and possible implications explored., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Carrying out any everyday task, be it driving in traffic, conversing with friends or playing basketball, requires rapid selection, integration and segregation of stimuli from different sensory modalities. At present, even the most advanced artificial intelligence-based systems are unable to replicate the multisensory processes that the human brain routinely performs, but how neural circuits in the brain carry out these processes is still not well understood. In this Perspective, we discuss recent findings that shed fresh light on the oscillatory neural mechanisms that mediate multisensory integration (MI), including power modulations, phase resetting, phase-amplitude coupling and dynamic functional connectivity. We then consider studies that also suggest multi-timescale dynamics in intrinsic ongoing neural activity and during stimulus-driven bottom-up and cognitive top-down neural network processing in the context of MI. We propose a new concept of MI that emphasizes the critical role of neural dynamics at multiple timescales within and across brain networks, enabling the simultaneous integration, segregation, hierarchical structuring and selection of information in different time windows. To highlight predictions from our multi-timescale concept of MI, real-world scenarios in which multi-timescale processes may coordinate MI in a flexible and adaptive manner are considered., (© 2024. Springer Nature Limited.)

The study aimed to develop and validate a gamified cognitive flexibility task through brain imaging, and to investigate behavioral and brain activation differences between young and older adults during task performance. Thirty-one young adults (aged 18-35) and 31 older adults (aged 60-80) were included in the present study. All participants underwent fMRI scans while completing the gamified cognitive flexibility task. Results showed that young adults outperformed older adults on the task. The left inferior frontal junction (IFJ), a key region of cognitive flexibility, was significantly activated during the task in both older and young adults. Comparatively, the percent signal change in the left IFJ was stronger in older adults than in young adults. Moreover, older adults demonstrated more precise representations during the task in the left IFJ. Additionally, the left inferior parietal lobule (IPL) and superior parietal lobule in older adults and the left middle frontal gyrus (MFG) and inferior frontal gyrus in young adults were also activated during the task. Psychophysiological interaction analyses showed significant functional connectivity between the left IFJ and the left IPL, as well as the right precuneus in older adults. In young adults, significant functional connectivity was found between the left IFJ and the left MFG, as well as the right angular. The current study provides preliminary evidence for the validity of the gamified cognitive flexibility task through brain imaging. The findings suggest that this task could serve as a reliable tool for assessing cognitive flexibility and for exploring age-related differences of cognitive flexibility in both brain and behavior., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: We propose a quantitative framework for motion-corrected T2 fetal brain measurements in vivo and validate the single-shot fast spin echo (SS-FSE) sequence to perform these measurements., Methods: Stacks of two-dimensional SS-FSE slices are acquired with different echo times (TE) and motion-corrected with slice-to-volume reconstruction (SVR). The quantitative T2 maps are obtained by a fit to a dictionary of simulated signals. The sequence is selected using simulated experiments on a numerical phantom and validated on a physical phantom scanned on a 1.5T system. In vivo quantitative T2 maps are obtained for five fetuses with gestational ages (GA) 21-35 weeks on the same 1.5T system., Results: The simulated experiments suggested that a TE of 400 ms combined with the clinically utilized TEs of 80 and 180 ms were most suitable for T2 measurements in the fetal brain. The validation on the physical phantom confirmed that the SS-FSE T2 measurements match the gold standard multi-echo spin echo measurements. We measured average T2s of around 200 and 280 ms in the fetal brain grey and white matter, respectively. This was slightly higher than fetal T2* and the neonatal T2 obtained from previous studies., Conclusion: The motion-corrected SS-FSE acquisitions with varying TEs offer a promising practical framework for quantitative T2 measurements of the moving fetus., (© 2024 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single-cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single-cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep-wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single-cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease., (© 2024 Wiley Periodicals LLC.)

Purpose: Detection and prediction of the rate of brain volume loss with age is a significant unmet need in patients with primary progressive multiple sclerosis (PPMS). In this study we construct detailed brain volume maps for PPMS patients. These maps compare age-related changes in both cortical and sub-cortical regions with those in healthy individuals., Methods: We conducted retrospective analyses of brain volume using T1-weighted Magnetic Resonance Imaging (MRI) scans of a large cohort of PPMS patients and healthy subjects. The volume of brain parenchyma (BP), cortex, white matter (WM), deep gray matter, thalamus, and cerebellum were measured using the robust SynthSeg segmentation tool. Age- and gender-related regression curves were constructed based on data from healthy subjects, with the 95% prediction interval adopted as the normality threshold for each brain region., Results: We analyzed 495 MRI scans from 169 PPMS patients, aged 20-79 years, alongside 563 exams from healthy subjects aged 20-86. Compared to healthy subjects, a higher proportion of PPMS patients showed lower than expected brain volumes in all regions except the cerebellum. The most affected areas were BP, WM, and thalamus. Lower brain volumes correlated with longer disease duration for BP and WM, and higher disability for BP, WM, cortex, and thalamus., Conclusions: Constructing age- and gender-related brain volume maps enabled identifying PPMS patients at a higher risk of brain volume loss. Monitoring these high-risk patients may lead to better treatment decisions and improve patient outcomes., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: Histone deacetylase 6 (HDAC6) has emerged as a therapeutic target for neurodegenerative diseases such as Alzheimer's disease. Noninvasive imaging of HDAC6 in the brain by positron emission tomography (PET) would accelerate research into its roles in these diseases. We recently discovered an 18 F-labeled derivative of the selective HDAC6 inhibitor SW-100 ([ 18 F]FSW-100) as a potential candidate for brain HDAC6 radioligand. As a mandatory step prior to clinical translation, we performed preclinical validation of [ 18 F]FSW-100., Methods: Process validation of [ 18 F]FSW-100 radiosynthesis for clinical use and assessment of preclinical toxicity and radiation dosimetry estimated from mouse distribution data were performed. In vitro selectivity of FSW-100 for 28 common receptors in the brain and HDAC isoforms was characterized. [ 18 F]FSW-100 PET imaging was performed in non-human primates in a conscious state to estimate the feasibility of HDAC6 imaging in humans., Results: Three consecutive validation runs of the automated radiosynthesis gave [ 18 F]FSW-100 injections with radiochemical yields of 12%, and the injections conformed to specified quality control criteria for batch release. No acute toxicity was observed for non-radiolabeled FSW-100 or radioactivity decayed [ 18 F]FSW-100 injection, and the former was negative in the Ames test. The whole-body effective dose estimated from biodistribution in mice was within the range of that of previously reported 18 F-radioligands in humans. In vitro selectivity against common receptors and other HDAC isoforms was confirmed. [ 18 F]FSW-100 demonstrated good penetration in monkey brain, and in vivo blocking studies suggested that the uptake was specific., Conclusion: These results support the clinical utility of [ 18 F]FSW-100 for in vivo imaging of HDAC6 in the brain., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Quantification of metabolites concentrations in institutional unit (IU) is important for inter-subject and long-term comparisons in the applications of magnetic resonance spectroscopy (MRS). Recently, deep learning (DL) algorithms have found a variety of applications on the process of MRS data. A quantification strategy compatible to DL base MRS spectral processing method is, therefore, useful., Materials and Methods: This study aims to investigate whether metabolite concentrations quantified using a convolutional neural network (CNN) based method, coupled with a scaling procedure that normalizes spectral signals for CNN input and linear regression, can effectively reflect variations in metabolite concentrations in IU across different brain regions with varying signal-to-noise ratios (SNR) and linewidths (LW). An error index based on standard error (SE) is proposed to indicate the confidence levels associated with metabolite predictions. In vivo MRS spectra were acquired from three brain regions of 43 subjects using a 3T system., Results: The metabolite concentrations in IU of five major metabolites, quantified using CNN and LCModel, exhibit similar ranges with Pearson's correlation coefficients ranging from 0.24 to 0.78. The SE of the metabolites shows a positive correlation with Cramer-Rao lower bound (CRLB) (r=0.46) and  absolute CRLB (r=0.81), calculated by multiplying CRLBs with the quantified metabolite content., Conclusion: In conclusion, the CNN based method with the proposed scaling procedures can be employed to quantify in vivo MRS spectra and derive metabolites concentrations in IU. The SE can be used as error index, indicating predicted uncertainties for metabolites and sharing information similar to the absolute CRLB., (© 2023. The Author(s), under exclusive licence to European Society for Magnetic Resonance in Medicine and Biology (ESMRMB).)

Background: Congenital anomalies of the kidney and urinary tract (CAKUT) represent 20-30% of all birth defects and are often associated with extra-renal malformations. We investigated the frequency of brain/spine malformations and neurological features in children with CAKUT., Methods: We reviewed the clinico-radiological and genetic data of 199 out of 1,165 children with CAKUT evaluated from 2006 to 2023 (99 males, mean age at MRI 6.4 years) who underwent brain and/or spine MRI. Patients were grouped according to the type of CAKUT (CAKUT-K involving the kidney and CAKUT-H involving the inferior urinary tract). Group comparisons were performed using χ 2 and Fisher exact tests., Results: Brain/spine malformations were observed in 101/199 subjects (50.7%), 8.6% (101/1165) of our CAKUT population, including midbrain-hindbrain anomalies (40/158, 25.3%), commissural malformations (36/158, 22.7%), malformation of cortical development (23/158, 14.5%), Chiari I anomaly (12/199, 6%), cranio-cervical junction malformations (12/199, 6%), vertebral defects (46/94, 48.9%), caudal regression syndrome (29/94, 30.8%), and other spinal dysraphisms (13/94, 13.8%). Brain/spine malformations were more frequent in the CAKUT-K group (62.4%, p < 0.001). Sixty-two subjects (62/199, 31.2%) had developmental delay/intellectual disability. Neurological examination was abnormal in 40/199 (20.1%). Seizures and/or electroencephalographic anomalies were reported in 28/199 (14%) and behavior problems in 19/199 subjects (9%). Developmental delay/intellectual disability was more frequent in kidney dysplasia (65.2%) and agenesis (40.7%) (p = 0.001)., Conclusions: We report a relative high frequency of brain/spine malformations and neurodevelopmental disorders in children with CAKUT who underwent MRI examinations in a tertiary referral center, widening the spectrum of anomalies associated with this condition., (© 2024. The Author(s), under exclusive licence to International Pediatric Nephrology Association.)

The purpose of this study was to assess the quality of clinical brain imaging in healthy subjects and patients on an FDA-approved commercial 0.55 T MRI scanner, and to provide information about the feasibility of using this scanner in a clinical workflow. In this IRB-approved study, brain examinations on the scanner were prospectively performed in 10 healthy subjects (February-April 2022) and retrospectively derived from 44 patients (February-July 2022). Images collected using the following pulse sequences were available for assessment: axial DWI (diffusion-weighted imaging), apparent diffusion coefficient maps, 2D axial fluid-attenuated inversion recovery images, axial susceptibility-weighted images (both magnitude and phase), sagittal T 1 -weighted (T1w) Sampling Perfection with Application Optimized Contrast images, sagittal T1w MPRAGE (magnetization prepared rapid gradient echo) with contrast enhancement, axial T1w turbo spin echo (TSE) with and without contrast enhancement, and axial T 2 -weighted TSE. Two readers retrospectively and independently evaluated image quality and specific anatomical features in a blinded fashion on a four-point Likert scale, with a score of 1 being unacceptable and 4 being excellent, and determined the ability to answer the clinical question in patients. For each category of image sequences, the mean, standard deviation, and percentage of unacceptable quality images (<2) were calculated. Acceptable (rating ≥ 2) image quality was achieved at 0.55 T in all sequences for patients and 85% of the sequences for healthy subjects. Radiologists were able to answer the clinical question in all patients scanned. In total, 50% of the sequences used in patients and about 60% of the sequences used in healthy subjects exhibited good (rating ≥ 3) image quality. Based on these findings, we conclude that diagnostic quality clinical brain images can be successfully collected on this commercial 0.55 T scanner, indicating that the routine brain imaging protocol may be deployed on this system in the clinical workflow., (© 2023 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

High-fat diet consumption for an extended period causes obesity, systemic metabolic disturbance, and brain insulin resistance, resulting in neuroinflammation. Although the beneficial effect of Cyclosorus terminans extract on obesity-related insulin resistance has been demonstrated, little is known about how it affects neuroinflammation and brain insulin resistance in obese rats. Male Wistar rats were given either a normal diet (ND, n = 6) or a high-fat diet (HFD, n = 24) for a total of 14 weeks. At the beginning of the week, 13 rats in the ND group were given vehicle orally for 2 weeks, while rats on HFD diets were randomized to one of four groups and given either vehicle, 100 mg/kg/day of Cyclosorus terminans extract, 200 mg/kg/day of Cyclosorus terminans extract, or 20 mg/kg/day of pioglitazone orally for 2 weeks. After the experimental period, blood and brain samples were taken to assess metabolic and brain parameters. HFD-fed rats had obesity, systemic and brain insulin resistance, brain inflammation, microglial and astrocyte hyperactivity, and brain necroptosis. Treatment with 200 mg/kg/day of Cyclosorus terminans extract and pioglitazone equally attenuated obesity, insulin resistance, brain insulin dysfunction, and neuroinflammation in insulin resistant rats. Our findings suggest that Cyclosorus terminans extract may hold promise as a therapeutic agent for insulin resistance and neuroinflammation in obese conditions., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Injury to the spinal cord of children may cause potential brain reorganizations, affecting their rehabilitation. However, the specific functional alterations of children after complete spinal cord injury (CSCI) remain unclear., Purpose: To explore the specific functional changes in local brain and the relationship with clinical characteristics in pediatric CSCI patients, clarifying the impact of CSCI on brain function in developing children., Study Type: Prospective., Subjects: Thirty pediatric CSCI patients (7.83 ± 1.206 years) and 30 age-, gender-matched healthy children as controls (HCs) (8.77 ± 2.079 years)., Field Strength/sequence: 3.0 T/Resting-state functional MRI (rs-fMRI) using echo-planar-imaging (EPI) sequence., Assessment: Amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) were used to characterize regional neural function., Statistical Tests: Two-sample t-tests were used to compare the ALFF, fALFF, ReHo values of the brain between pediatric CSCI and HCs (voxel-level FWE correction, P < 0.05). Spearman correlation analyses were performed to analyze the associations between the ALFF, fALFF, ReHo values in altered regions and the injury duration, sensory motor scores of pediatric CSCI patients (P < 0.05). Then receiver operating characteristic (ROC) analysis was conducted to identify possible sensitive imaging indicators for clinical therapy., Results: Compared with HCs, pediatric CSCI showed significantly decreased ALFF in the right postcentral gyrus (S1), orbitofrontal cortex, and left superior temporal gyrus (STG), increased ALFF in bilateral caudate nucleus, thalamus, middle cingulate gyrus, and cerebellar lobules IV-VI, and increased ReHo in left cerebellum Crus II and Brodmann area 21. The ALFF value in the right S1 negatively correlated with the pinprick and light touch sensory scores of pediatric CSCI. When the left STG was used as an imaging biomarker for pediatric CSCI, it achieved the highest area under the curve of 0.989., Conclusions: These findings may provide potential neural mechanisms for sensory motor and cognitive-emotional deficits in children after CSCI., Evidence Level: 2 TECHNICAL EFFICACY: Stage 5., (© 2023 International Society for Magnetic Resonance in Medicine.)

Attention, working memory, and executive control are commonly considered distinct cognitive functions with important reciprocal interactions. Yet, longstanding evidence from lesion studies has demonstrated both overlap and dissociation in their behavioural expression and anatomical underpinnings, suggesting that a lower dimensional framework could be employed to further identify processes supporting goal-directed behaviour. Here, we describe the anatomical and functional correspondence between attention, working memory, and executive control by providing an overview of cognitive models, as well as recent data from lesion studies, invasive and non-invasive multimodal neuroimaging and brain stimulation. We emphasize the benefits of considering converging evidence from multiple methodologies centred on the identification of brain mechanisms supporting goal-driven behaviour. We propose that expanding on this approach should enable the construction of a comprehensive anatomo-functional framework with testable new hypotheses, and aid clinical neuroscience to intervene on impairments of executive functions., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

A growing body of evidence indicates the existence of abnormal local and long-range functional connection patterns in patients with alcohol use disorder (AUD). However, it has yet to be established whether AUD is associated with abnormal interhemispheric and intrahemispheric functional connection patterns. In the present study, we analysed resting-state functional magnetic resonance imaging data from 55 individuals with AUD and 32 healthy nonalcohol users. For each subject, whole-brain functional connectivity density (FCD) was decomposed into ipsilateral and contralateral parts. Correlation analysis was performed between abnormal FCD and a range of clinical measurements in the AUD group. Compared with healthy controls, the AUD group exhibited a reduced global FCD in the anterior and middle cingulate gyri, prefrontal cortex and thalamus, along with an enhanced global FCD in the temporal, parietal and occipital cortices. Abnormal interhemispheric and intrahemispheric FCD patterns were also detected in the AUD group. Furthermore, abnormal global, contralateral and ipsilateral FCD data were correlated with the mean amount of pure alcohol and the severity of alcohol addiction in the AUD group. Collectively, our findings indicate that global, interhemispheric and intrahemispheric FCD may represent a robust method to detect abnormal functional connection patterns in AUD; this may help us to identify the neural substrates and therapeutic targets of AUD., (© 2024 The Authors. Addiction Biology published by John Wiley & Sons Ltd on behalf of Society for the Study of Addiction.)

Vascular aging influences hemodynamics, elevating risks for vascular diseases and dementia. We recently demonstrated that knockout (KO) of Dusp5 enhances cerebral and renal hemodynamics and cognitive function. This improvement correlates with elevated pPKC and pERK1/2 levels in the brain and kidneys. Additionally, we observed that Dusp5 KO modulates the passive mechanical properties of cerebral and renal arterioles, associated with increased myogenic tone at low pressure, enhanced distensibility, greater compliance, and reduced stiffness. The present study evaluates the structural and mechanical properties of the middle cerebral artery (MCA) in Dusp5 KO rats. We found that vascular smooth muscle cell layers and the collagen content in the MCA wall are comparable between Dusp5 KO and control rats. The internal elastic lamina in the MCA of Dusp5 KO rats exhibits increased thickness, higher autofluorescence intensity, smaller fenestrae areas, and fewer fenestrations. Despite an enhanced myogenic response and tone of the MCA in Dusp5 KO rats, other passive mechanical properties, such as wall thickness, cross-sectional area, wall-to-lumen ratio, distensibility, incremental elasticity, circumferential wall stress, and elastic modulus, do not significantly differ between strains. These findings suggest that while Dusp5 KO has a limited impact on altering the structural and mechanical properties of MCA, its primary role in ameliorating hemodynamics and cognitive functions is likely attributable to its enzymatic activity on cerebral arterioles. Further research is needed to elucidate the specific enzymatic mechanisms and explore potential clinical applications in the context of vascular aging., (© 2024. The Author(s), under exclusive licence to American Aging Association.)

Background and Purpose: We aimed to explore structural connectivity in status epilepticus., Methods: We enrolled participants who underwent diffusion tensor imaging. We applied graph theory to investigate structural connectivity. We compared the structural connectivity measures between patients and healthy controls and between patients with poor (modified Rankin Scale [mRS] >3) and good (mRS ≤3) admission outcomes., Results: We enrolled 28 patients and 31 healthy controls (age 65.5 vs.62.0 years, p = .438). Of these patients, 16 and 12 showed poor and good admission outcome (age 65.5 vs.62.0 years, p = .438). The assortative coefficient (-0.113 vs. -0.121, p = .021), mean clustering coefficient (0.007 vs.0.006, p = .009), global efficiency (0.023 vs.0.020, p = .009), transitivity (0.007 vs.0.006, p = .009), and small-worldness index (0.006 vs.0.005, p = .021) were higher in patients with status epilepticus than in healthy controls. The assortative coefficient (-0.108 vs. -0.119, p = .042), mean clustering coefficient (0.007 vs.0.006, p = .042), and transitivity (0.008 vs.0.007, p = .042) were higher in patients with poor admission outcome than in those with good admission outcome. MRS score was positively correlated with structural connectivity measures, including the assortative coefficient (r = 0.615, p = .003), mean clustering coefficient (r = 0.544, p = .005), global efficiency (r = 0.515, p = .007), transitivity (r = 0.547, p = .007), and small-worldness index (r = 0.435, p = .024)., Conclusion: We revealed alterations in structural connectivity, showing increased integration and segregation in status epilepticus, which might be related with neuronal synchronization. This effect was more pronounced in patients with a poor admission outcome, potentially reshaping our understanding for comprehension of status epilepticus mechanisms and the development of more targeted treatments., (© 2024 American Society of Neuroimaging.)

Alzheimer's disease (AD) is the most common form of dementia. Obesity in middle age increases AD risk and severity, which is alarming given that obesity prevalence peaks at middle age and obesity rates are accelerating worldwide. Midlife, but not late-life obesity increases AD risk, suggesting that this interaction is specific to preclinical AD. AD pathology begins in middle age, with accumulation of amyloid beta (Aβ), hyperphosphorylated tau, metabolic decline, and neuroinflammation occurring decades before cognitive symptoms appear. We used a transcriptomic discovery approach in young adult (6.5 months old) male and female TgF344-AD rats that overexpress mutant human amyloid precursor protein and presenilin-1 and wild-type (WT) controls to determine whether inducing obesity with a high-fat/high-sugar "Western" diet during preclinical AD increases brain metabolic dysfunction in dorsal hippocampus (dHC), a brain region vulnerable to the effects of obesity and early AD. Analyses of dHC gene expression data showed dysregulated mitochondrial and neurotransmission pathways, and up-regulated genes involved in cholesterol synthesis. Western diet amplified the number of genes that were different between AD and WT rats and added pathways involved in noradrenergic signaling, dysregulated inhibition of cholesterol synthesis, and decreased intracellular lipid transporters. Importantly, the Western diet impaired dHC-dependent spatial working memory in AD but not WT rats, confirming that the dietary intervention accelerated cognitive decline. To examine later consequences of early transcriptional dysregulation, we measured dHC monoamine levels in older (13 months old) AD and WT rats of both sexes after long-term chow or Western diet consumption. Norepinephrine (NE) abundance was significantly decreased in AD rats, NE turnover was increased, and the Western diet attenuated the AD-induced increases in turnover. Collectively, these findings indicate obesity during prodromal AD impairs memory, potentiates AD-induced metabolic decline likely leading to an overproduction of cholesterol, and interferes with compensatory increases in NE transmission., (© 2023 International Society for Neurochemistry.)