Search Results (4,177)

Background: Chemotherapy-induced peripheral neuropathy (CIPN) is a common, disabling toxicity with no validated biomarkers. MRI-based functional neuroimaging could offer insight into central pain processing and may reveal reproducible brain signatures of CIPN. Methods: Following PRISMA 2020 (PROSPERO: CRD420251132102), we systematically reviewed whole-brain MRI studies in adult cancer patients with CIPN. Eligible MRI techniques included task-based fMRI, resting-state fMRI, perfusion MRI, and structural MRI. Data were synthesized through voxelwise activation likelihood estimation (ALE), systems-level region-of-interest (ROI) mapping, and proportion meta-analysis of regional involvement. Results: Of 2488 screened records, five observational studies were included. The voxelwise ALE analysis did not identify clusters surviving correction, but dispersed foci appeared within the default mode network (DMN), prefrontal executive cortex, and primary sensorimotor regions, suggesting the engagement of these pain-processing networks. ROI synthesis confirmed consistent alterations in the DMN and executive prefrontal and sensorimotor cortices in CIPN patients compared with controls, while the brainstem/periaqueductal gray and cerebellum were rarely implicated. Proportion meta-analysis further quantified these differences: CIPN patients showed altered involvement in 30% (95% CI 0.16–0.48) of contrasts, with the highest frequencies in the DMN (50%), sensorimotor (33%), and executive prefrontal regions (33%). By contrast, control-higher contrasts were less frequent (10%, 95% CI 0.03–0.27), highlighting CIPN-related increases particularly in self-referential and somatosensory networks. Conclusions: Across analytic approaches, CIPN is characterized by reproducible alterations in the DMN and executive prefrontal and sensorimotor networks. These central pain signatures represent promising MRI-based biomarkers for identifying and monitoring CIPN in oncology. Full article

Ischemic stroke remains a leading cause of global mortality and long-term neurological disability, where the “Time is Brain” paradigm dictates that rapid and accurate lesion assessment is fundamental for effective clinical intervention. While the nnU-Net v2 framework has established a new state of the art in medical image segmentation, its high computational demands and reliance on data-center-grade GPUs hinder its translation into real-time, point-of-care clinical workflows. This study presents a technical feasibility analysis of a Cloud-to-Edge optimization pipeline designed to transfer a 3D nnU-Net v2 model from a high-performance cloud environment to a resource-constrained embedded device. Experimental results showed that edge deployment was associated with a reduction in overlap-based segmentation metrics compared with the cloud reference, with Dice decreasing from approximately 0.78 to 0.67. However, TensorRT FP32 and FP16 inference produced nearly identical mean segmentation metrics, suggesting that reduced-precision inference did not introduce additional measurable degradation under the evaluated conditions. The optimized FP16 configuration achieved a processing time of 10.2 s per 3D volume, representing a 33% reduction compared with embedded FP32 inference, while operating within a low-power envelope of approximately 10–13 W. These findings support the preliminary technical feasibility of executing advanced 3D volumetric segmentation models on low-power edge hardware. Nevertheless, the evaluation was limited to an internal 25-case test subset and did not include external validation, prospective clinical assessment, or reader studies. Therefore, the proposed system should be interpreted as a preliminary deployment framework rather than a clinically validated tool for autonomous stroke imaging. Full article

The rapid expansion of artificial intelligence has intensified the demand for hardware systems capable of emulating brain-like information processing with high accuracy, energy efficiency, and reliability. Neuromorphic computing based on memristive artificial synapses has emerged as a promising approach to overcome the limitations of conventional von Neumann architectures. Although inorganic and oxide-based synaptic memristors have been widely explored for neuromorphic systems, they often suffer from poor linearity, asymmetric potentiation/depression behavior, limited conductance states, and device variability, which restrict learning accuracy and scalability. In contrast, polymer-based memristors have gained significant attention owing to their intrinsic advantages, including mechanical flexibility, molecular tunability, controllable electronic/ionic transport, low-temperature processability, and compatibility with large-area fabrication. This review critically examines recent advances in polymer—based memristive materials and devices for achieving linear and symmetric artificial synaptic behavior. Polymer synapses are classified into pure polymer, polymer composite, and polymer-hybrid systems through a mechanism to function framework. Rather than providing a general compilation of organic memristor studies, this review analyzes how polymer chemistry, ion-migration control, trap state distribution, redox activity, electrode selection, active layer thickness, and interface engineering govern conductance update linearity, symmetry, and uniformity. Fundamental switching mechanisms, material classifications, device architectures, key synaptic characteristics, and system-level neuromorphic performance, including pattern-recognition applications, are critically discussed. By explicitly linking material and device design to conductance update fidelity, learning accuracy, training convergence, and pattern-recognition reliability, this review provides practical design guidelines and future perspectives for next-generation polymer-based neuromorphic hardware with improved linearity, symmetry, reliability, and scalability. Full article

Background/Objectives: Intentional inhibition reflects voluntary control abilities and is assumed to be an indicator of overweight. The medial frontal cortex is an important brain region associated with intentional inhibition. Nevertheless, it is uncertain whether being overweight is connected to impaired food-related intentional inhibition (FII), and if so, what its underlying neural correlates are. The present study therefore aims to provide increased support for overweight due to impairment of FII. Methods: Firstly, 55 overweight and 45 normal-weight college students (Sample 1) were instructed to perform a go/no-go/choose task, which included a resting-state fMRI. Neural correlates of FII were examined using regional homogeneity (ReHo) analyses. Subsequently, an additional 180 undergraduates (87 overweight and 93 normal-weight; Sample 2) were examined to ascertain the differences in resting-state functional connectivity (rsFC) between overweight and normal-weight participants. The study also investigated whether restrained eating mediated the effect of rsFCs on one-year body index changes. Results: FII demonstrated a positive correlation with the cerebellum, inferior temporal gyrus, orbitofrontal cortex, inferior frontal gyrus, and cingulate gyrus. Additionally, in comparison with participants with normal weight, overweight participants demonstrated diminished rsFC between the FII-related areas and the postcentral gyrus, while heightened rsFC strengths were found between these areas and the middle temporal gyrus and precuneus. Furthermore, mediation analyses demonstrated that cingulate–precuneus connectivity is linked to fat mass index change a year later through restrained eating. Conclusions: FII was associated with connectivity between brain regions involved in inhibitory control and maladaptive eating. Furthermore, we investigated how these connectivity patterns could potentially affect future body fat loss through restrained eating. Full article

Impairment in blood supply to the brain deprives its cells of the much-needed nutrients and molecules such as oxygen and glucose necessary for its development, growth and survival. This will set up a host of pathological processes such as impaired homeostasis, energy failure, excitotoxicity, oxidative stress, impaired protein synthesis, inflammation, cytokine-mediated toxicity and impairment of blood–brain barrier. These pathological processes will result in the damage or death of the cells depending on the extent of the deprivation. Similarly, they will impair synthesis of acetylcholine (Ach) and norepinephrine (NE), which are important neurotransmitters in the cholinergic and adrenergic systems responsible for cellular communication and functions. Thus, interventions to help arrest and/or modulate the initial and subsequent pathological states and help recover the functions of the brain are needed. One of such interventions is vagus nerve stimulation, which helps activate the cholinergic and the adrenergic systems via projections of the afferent fibers of the vagus nerve to the nucleus of the solitary tract (NTS). Activation of the cholinergic and the adrenergic systems results in reduction in pro-inflammatory factors such as tumor necrosis α, increase in pro-angiogenic factors and increase in firing of adrenergic neurons in the central nervous system (CNS). Full article

Background: Mild traumatic brain injury (mTBI) is frequently followed by persistent cognitive, affective, and sensory complaints despite unremarkable conventional structural imaging. Resting-state functional MRI (rs-fMRI) has been increasingly employed to detect subtle alterations in large-scale brain networks. However, variability in analytical approaches and the potential influence of neurovascular factors complicate interpretation of BOLD-derived connectivity findings. Objective: This study provides a focused, evidence-informed synthesis integrating umbrella review principles with a targeted narrative analysis of recent high-quality rs-fMRI studies in mild traumatic brain injury (mTBI). Rather than a comprehensive systematic review, the aim was to identify convergent patterns of network dysfunction while critically examining methodological constraints, including neurovascular confounds and variability in analytical approaches. Conclusions: This synthesis supports a network-level model of mTBI characterized by distributed connectivity disturbances. However, given the limited number of eligible studies and substantial methodological heterogeneity, findings should be interpreted as qualitative convergence rather than quantitative generalization. Future longitudinal, multimodal, and standardized imaging approaches are required to clarify the translational relevance of rs-fMRI findings. Full article

Background: Chronic critical illness (CCI) following acute brain injury involves persistent immune dysfunction, yet its genetic determinants remain unclear. We investigated whether the rate of T-cell receptor excision circle (TREC) depletion—a proposed marker of adaptive homeostatic resilience—is associated with the burden of rare damaging genetic variants. Methods: Whole-exome sequencing (WES) was performed on a cohort of 84 patients (64 with traumatic brain injury, 20 with stroke). In a longitudinal sub-cohort (n = 27), patients were stratified into quartiles (Q1–Q4) based on the slope of their TREC trajectories. ‘Qualifying variants’ (QVs) were defined using strict rarity (gnomAD allele frequency ≤ 0.001) and pathogenicity criteria. Gene-level burden (collapsing) analysis and permutation-based statistical testing (10,000 iterations) were employed to evaluate genetic enrichment in the extreme quartiles. Results: While baseline TREC levels were strictly age dependent (p < 0.0001), the rate of change (TREC slope) was age independent. Rapid TREC decline (Q1) correlated with significantly higher final SOFA scores (p = 0.001) and neutrophil-to-lymphocyte ratios (p = 0.020). Rare variant burden analysis revealed that Q1 patients were significantly more likely to harbor QVs in immune-related genes compared to the Q4 recovery group (odds ratio = 8.25; permutation p = 0.016). Patients with rapid decline were enriched for QVs in putative core “housekeeping” pathways essential for T-cell maintenance and DNA repair (e.g., ERCC3, FANCM), whereas variants in recovering patients were restricted to peripheral effector or structural pathways. Conclusions: Our findings suggest, as a conceptual framework, that an individual’s ability to maintain T-cell homeostasis during critical illness is influenced by their underlying genetic buffering capacity. We propose a hypothetical “two-hit” framework where physiological stress unmasks pre-existing fragilities in core homeostatic pathways—potentially reflecting a state of functional haploinsufficiency under extreme proliferative demand—leading to accelerated immune exhaustion. These results position the TREC slope as a dynamic, age-independent biomarker of genomic resilience in the ICU. All findings are exploratory and hypothesis generating. Full article

Acetylcholine (ACh) is an evolutionarily conserved neurotransmitter that is widely distributed in the central and peripheral nervous systems and plays essential roles in multiple physiological processes. This review summarizes the full biological cycle of ACh, including its synthesis, vesicular storage, release, degradation, and reuptake, and discusses the regulatory mechanisms underlying its functions in the nervous system and peripheral organs. Through nicotinic acetylcholine receptors (nAChRs) and muscarinic acetylcholine receptors (mAChRs), ACh is involved in central nervous system functions such as cognition, learning and memory, attention, arousal, reward, and decision-making, as well as peripheral processes including motor control, autonomic regulation, and immune modulation. In addition, ACh plays a pivotal role in the brain–body axis. At the central level, the nervous system regulates peripheral organ function through autonomic and neuroendocrine pathways. At the peripheral level, cholinergic signals derived from the enteric nervous system and immune cells convey information about the body’s internal state to the central nervous system through vagal and other afferent pathways, forming an important bottom-up regulatory network. Collectively, these findings indicate that ACh is not only a classical neurotransmitter but also a key molecular mediator of brain–body communication. A more comprehensive understanding of cholinergic signaling may provide new insights into physiological regulation and the pathogenesis of neurological, psychiatric, cardiovascular, and inflammatory diseases. Full article

Theta oscillations, neural activity within the 4–8 Hz range, are implicated in a wide range of cognitive functions, including oculomotor and sensory processing, attention, memory, and motor planning and execution across diverse brain regions. Saccadic eye movements (SEMs), which are integral to visual perception and cognition, occur within a similar frequency range. This review explores how theta oscillations contribute to oculomotor and cognitive processing, emphasizing their role in coordinated motor and sensory functions. We synthesize foundational and contemporary studies into a working model describing neural synchronization across cognitive networks. We discuss the complex interplay between theta oscillations, SEMs, and cognition, summarizing the current state of our knowledge. Full article

Background: Accurate brain tumor segmentation from Magnetic Resonance Imaging (MRI) depends on the fusion of multiple complementary modalities. However, clinical practice often faces incomplete modality sets due to acquisition failures, patient contraindications, or protocol variations. Current methods either treat each modality feature extractor in isolation or depend on computationally expensive teacher networks for cross-modal knowledge transfer. Objective: This paper presents Hierarchical Adaptive Group Self-Support Learning with Boundary-Aware Calibration (HAGSS), a framework that overcomes three key limitations of existing group self-support methods: static group formation that ignores temporal prediction quality, uniform treatment of boundary and interior voxels, and distribution mismatch across heterogeneous modality logits. Methods: We propose a hierarchical adaptive group formation mechanism that reassigns group leader roles at each epoch based on voxel-level prediction confidence scores instead of fixed sensitivity priors. We also introduce a boundary-aware calibration module that applies spatially varied distillation weights with greater emphasis on tumor boundary regions. In addition, we design a cross-scale consistency regularization term that enforces agreement between multi-resolution predictions to stabilize the self-support target. Results: Experiments on BraTS2020, BraTS2018, and BraTS2021 datasets show that HAGSS achieves consistent improvements over state-of-the-art baselines. The average Dice gains across the whole tumor, tumor core, and enhancing tumor regions reach 1.30% on BraTS2020 and 1.61% on BraTS2021 compared to existing methods. All improvements are statistically significant ($p<0.05$). Conclusions: HAGSS operates exclusively during training, adds no parameters or inference cost, and can be applied as a plug-in module to any multi-encoder incomplete multi-modal segmentation architecture. Code is publicly available at GitHub. Full article

Driven by global energy transformation and the progress of artificial intelligence technology, traditional automotive engineering is undergoing profound changes. Transportation is rapidly advancing toward electrification and intelligence. Against this background, this paper identifies three emerging paradigms for the development of electric vehicles: Heart Revolution, Brain Evolution, and Network Integration. This paper points out that automobiles are evolving from traditional one-way energy consumers to dynamic energy nodes in smart grids. With the support of artificial intelligence technology, the role of automobiles is also shifting from a simple means of transportation to an intelligent mobile terminal. At the same time, this paper focuses on analyzing the application of the integration theory of “Four Networks and Four Flows” in automobile upgrading. The theory does not focus on the optimization of a single node unit but emphasizes a systematic perspective to improve overall performance and support sustainable development. This paper suggests that the development of the automobile industry must be deeply integrated with the humanity world, information world and physical world. By building a five-in-one architecture of “Human–Vehicle–Road–Cloud–Satellite”, the automobile industry could follow a practical pathway toward coordinated development. At the same time, breakthroughs in core technologies such as solid-state batteries and wide-bandgap semiconductors are also imminent. This paper aims to provide a sustainable and high-performance automobile development path and integrate the concept of human-oriented design into it. Meanwhile, China’s new energy vehicle industry is used as a representative context to illustrate its engineering and industrial implementation. Full article

Background: Radio Electric Asymmetric Conveyer (REAC) neurobiological modulation is proposed as an approach designed to interact with endogenous bioelectrical processes involved in cortical regulation. However, its electrophysiological correlates in physiologically preserved neural systems remain insufficiently characterized. The present study explored whether a standardized REAC Brain Wave Optimization Gamma (BWO-G_B) protocol is associated with measurable changes in resting-state EEG activity in healthy adults. Methods: Nine neurologically healthy participants completed a standardized REAC BWO-G_B protocol consisting of 18 sessions administered over six consecutive days. Resting-state EEG recordings were obtained before and after the intervention. Spectral power was analyzed across the 1–100 Hz range. Multivariate organization of cortical activity was explored using Principal Component Analysis (PCA) and Canonical Discriminant Analysis (CDA), with CDA used only as a descriptive visualization of within-dataset multivariate organization. Cross-correlation analysis was applied to evaluate changes in inter-regional temporal synchronization. Individual-level non-parametric testing (Wilcoxon signed-rank test) was conducted only to characterize within-subject directional spectral modulation across the recorded montage. Results: Post-intervention EEG recordings showed a consistent redistribution of spectral power across cortical regions, predominantly within frequencies below approximately 20 Hz. This pattern was observed across subjects at the individual level. Multivariate analysis revealed a dissociation between PCA, which showed partial overlap between conditions, and CDA, which descriptively showed within-dataset separability between baseline and post-intervention cortical states. Cross-correlation analysis indicated a spatially differentiated redistribution of temporal synchronization across cortical regions. At the individual level, descriptive Wilcoxon analyses indicated broadband spectral differences in seven of nine participants (p < 0.05), with consistent directional trends across all subjects; these p-values should not be interpreted as confirmatory statistical evidence. Conclusions: The findings indicate the presence of a reproducible electrophysiological pattern observed after completion of the REAC BWO-G_B protocol in healthy adults. The observed combination of spectral redistribution, descriptive multivariate organization, and changes in temporal synchronization is consistent with a structured post-intervention modification of cortical activity organization within the present dataset. However, given the exploratory design, small sample size, absence of a control condition, and absence of objective vigilance monitoring, these results should be interpreted cautiously and should not be considered as evidence of intervention-specific effects. Further controlled studies are required to determine specificity, underlying mechanisms, and potential functional relevance. Full article

Background: Human dental pulp stem cells (hDPSCs) are a promising source of multipotent mesenchymal stem cells (MSCs) for regenerative neurology because of their inherent neurogenic potential. However, robust and reproducible protocols for driving their terminal neuronal maturation in a fully defined, xeno-free environment are lacking. Methods: hDPSCs were isolated from a donor tooth and characterized for mesenchymal (CD105, CD90, CD73, CD13) and stemness-associated markers (SOX2, Oct3/4 and Nanog). Cells were differentiated in a novel, fully chemically defined medium 1% ITS medium (ITS: Insulin, Transferrin, Selenium) supplemented with glial cell line-derived neurotrophic factor (GDNF) or brain-derived neurotrophic factor (BDNF). Neuronal commitment and partial maturation were assessed via immunofluorescence, Western blot, and RT-PCR for markers such as NeuN (Neuronal nuclei) and NF-M (Neurofilament medium chain), and functionally by whole-cell patch-clamp electrophysiology. Results: Although undifferentiated hDPSCs expressed neural progenitor markers (βIII-tubulin and Nestin), only GDNF treatment in a chemically defined medium significantly upregulated mature neuronal markers (NeuN and NF-M) and downregulated mesenchymal markers. Importantly, GDNF-treated cells exhibited key functional changes, including hyperpolarized resting membrane potentials, increased membrane capacitance, and elevated input resistance, which are electrophysiological hallmarks of neural precursor or early neuronal maturation, compared to control cells cultured in medium containing fetal bovine serum (FBS). Although action potentials were not elicited, this represents a significant advancement toward achieving a functional neuronal state. Conclusion: This study demonstrates that a fully chemically defined medium enables GDNF to drive hDPSCs beyond the neural progenitor state towards a partially mature neuronal phenotype. This defined medium protocol eliminates serum variability, enhances reproducibility, and provides a critical step towards standardizing hDPSC-derived neuronal cells for disease modeling and cell-based therapy. Full article

Background/Objectives: Cortical spreading depolarization (SD) is recognized as the pathophysiological substrate of migraine aura. Suppression of ongoing cortical activity produced by SD is thought to underlie the transient neurological deficits characteristic of the aura phase. While cortical hyperexcitability is a well-established feature of migraine brain, the effect of SD on spontaneous electrical activity in the hyperexcitable cortex remains poorly understood. Here, we investigate how SD and SD-induced depression of cortical activity are modulated by a state of mildly enhanced excitability. Methods: Using freely behaving rats, we assessed characteristics of SDs, electrocorticographic spectral power in the frontal and occipital cortices during interictal period and after SD initiation, under both drug-free conditions and following mild pharmacological disinhibition. Results: Mild cortical disinhibition resulted in a significant increase in baseline oscillatory power relative to control conditions. While cortical hyperexcitability did not alter the properties of SD itself, it differentially modulated the impact of SD on spontaneous activity in a region-specific manner. Notably, under conditions of enhanced excitability, the duration of SD-induced depression was markedly reduced in the frontal cortex but prolonged in the occipital cortex. Conclusions: These findings demonstrate that the effects of SD on spontaneous cortical activity are critically dependent on the baseline level of cortical excitability and exhibit distinct regional heterogeneity. In the awake, hyperexcitable state, the occipital cortex shows heightened vulnerability to SD-induced depression, a finding that may provide a mechanistic basis for the disproportionate involvement of the occipital cortex in aura generation and the predominance of visual symptoms in migraine aura. Full article

Methylmercury (MeHg) is a potent environmental contaminant primarily ingested through seafood consumption. Gestational exposure induces profound neurological and developmental deficits in the fetus that often persist throughout childhood. This developmental vulnerability arises from the immature state of the blood–brain barrier and a limited endogenous antioxidant capacity in the developing CNS. Postnatal exposure via breastfeeding further compromises neurodevelopment, specifically impairing visuospatial processing and memory. While fetal and placental mercury accumulation correlates with gestational age, the specific mechanisms of transplacental transport remain poorly defined. Mechanistically, MeHg predominantly accumulates in fetal renal tissue, followed by the brain and liver. This review aims to elucidate MeHg-induced oxidative stress and autophagic collapse mediated by the PI3K/AKT/mTOR and AMPK/TSC2/mTOR pathways. Furthermore, we evaluate neuroprotective candidates, specifically N-acetyl-L-cysteine (NAC) and CCL chemokine modulation, as strategies to mitigate fetal impairment and the associated cellular damage. Full article