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In the latter, NfL demonstrated a good diagnostic and prognostic accuracy and a potential value as a marker of proximity to clinical onset in pre-symptomatic PRNP mutation carriers. Similarly, in Alzheimer's disease and other NDs, higher NfL concentrations seem to predict a faster disease progression. While increasing evidence indicates a potential clinical value of NfL in monitoring cerebrovascular disease, the association between NfL and prediction of outcome and/or disease activity in autoimmune encephalitis and infectious diseases has only been investigated in few cohorts and deserves confirmatory studies. In the era of precision medicine and evolving therapeutic options, CSF and blood NfL might aid the diagnostic and prognostic assessment of RPDs and the stratification and management of patients according to disease progression in clinical trials.Many neurodegenerative diseases are associated with chronic inflammation in the brain and periphery giving rise to a continuous imbalance of immune processes. Next to inflammation markers, activation of transposable elements, including long intrespersed nuclear elements (LINE) elements and endogenous retroviruses (ERVs), has been identified during neurodegenerative disease progression and even correlated with the clinical severity of the disease. Azeliragon ERVs are remnants of viral infections in the human genome acquired during evolution. Upon activation, they produce transcripts and the phylogenetically youngest ones are still able to produce viral-like particles. In addition, ERVs can bind transcription factors and modulate immune response. Being between own and foreign, ERVs are reviewed in the context of viral infections of the central nervous system, in aging and neurodegenerative diseases. Moreover, this review tests the hypothesis that viral infection may be a trigger at the onset of neuroinflammation and that ERVs sustain the inflammatory imbalance by summarizing existing data of neurodegenerative diseases associated with viruses and/or ERVs.Across sleep and wakefulness, brain function requires inter-neuronal interactions lasting beyond seconds. Yet, most studies of neural circuit connectivity focus on millisecond-scale interactions mediated by the classic fast transmitters, GABA and glutamate. In contrast, neural circuit roles of the largest transmitter family in the brain-the slow-acting peptide transmitters-remain relatively overlooked, or described as "modulatory." Neuropeptides may efficiently implement sustained neural circuit connectivity, since they are not rapidly removed from the extracellular space, and their prolonged action does not require continuous presynaptic firing. From this perspective, we review actions of evolutionarily-conserved neuropeptides made by brain-wide-projecting hypothalamic neurons, focusing on lateral hypothalamus (LH) neuropeptides essential for stable consciousness the orexins/hypocretins. Action potential-dependent orexin release inside and outside the hypothalamus evokes slow postsynaptic excitation. This excitation does not arise from modulation of classic neurotransmission, but involves direct action of orexins on their specific G-protein coupled receptors (GPCRs) coupled to ion channels. While millisecond-scale, GABA/glutamate connectivity within the LH may not be strong, re-assessing LH microcircuits from the peptidergic viewpoint is consistent with slow local microcircuits. The sustained actions of neuropeptides on neuronal membrane potential may enable core brain functions, such as temporal integration and the creation of lasting permissive signals that act as "eligibility traces" for context-dependent information routing and plasticity. The slowness of neuropeptides has unique advantages for efficient neuronal processing and feedback control of consciousness.Autism spectrum disorders (ASDs) are a spectrum of neurodevelopmental disorders characterized by impaired social interaction and communication, as well as stereotyped and repetitive behaviors. ASDs affect nearly 2% of the United States child population and the worldwide prevalence has dramatically increased in recent years. The etiology is not clear but ASD is thought to be caused by a combination of intrinsic and extrinsic factors. Circadian rhythms are the ∼24 h rhythms driven by the endogenous biological clock, and they are found in a variety of physiological processes. Growing evidence from basic and clinical studies suggest that the dysfunction of the circadian timing system may be associated with ASD and its pathogenesis. Here we review the findings that link circadian dysfunctions to ASD in both experimental and clinical studies. We first introduce the organization of the circadian system and ASD. Next, we review physiological indicators of circadian rhythms that are found disrupted in ASD individuals, including sleep-wake cycles, melatonin, cortisol, and serotonin. Finally, we review evidence in epidemiology, human genetics, and biochemistry that indicates underlying associations between circadian regulation and the pathogenesis of ASD. In conclusion, we propose that understanding the functional importance of the circadian clock in normal and aberrant neurodevelopmental processes may provide a novel perspective to tackle ASD, and clinical treatments for ASD individuals should comprise an integrative approach considering the dynamics of daily rhythms in physical, mental, and social processes.Multimodal heterogeneous data, such as structural magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF), are effective in improving the performance of automated dementia diagnosis by providing complementary information on degenerated brain disorders, such as Alzheimer's prodromal stage, i.e., mild cognitive impairment. Effectively integrating multimodal data has remained a challenging problem, especially when these heterogeneous data are incomplete due to poor data quality and patient dropout. Besides, multimodal data usually contain noise information caused by different scanners or imaging protocols. The existing methods usually fail to well handle these heterogeneous and noisy multimodal data for automated brain dementia diagnosis. To this end, we propose a high-order Laplacian regularized low-rank representation method for dementia diagnosis using block-wise missing multimodal data. The proposed method was evaluated on 805 subjects (with incomplete MRI, PET, and CSF data) from the real Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Experimental results suggest the effectiveness of our method in three tasks of brain disease classification, compared with the state-of-the-art methods.Learning to play a musical instrument is a complex task that integrates multiple sensory modalities and higher-order cognitive functions. Therefore, musical training is considered a useful framework for the research on training-induced neuroplasticity. However, the classical nature-or-nurture question remains, whether the differences observed between musicians and non-musicians are due to predispositions or result from the training itself. Here we present a review of recent publications with strong focus on experimental designs to better understand both brain reorganization and the neuronal markers of predispositions when learning to play a musical instrument. Cross-sectional studies identified structural and functional differences between the brains of musicians and non-musicians, especially in regions related to motor control and auditory processing. A few longitudinal studies showed functional changes related to training while listening to and producing music, in the motor network and its connectivity with the auditory system, in line with the outcomes of cross-sectional studies. Parallel changes within the motor system and between the motor and auditory systems were revealed for structural connectivity. In addition, potential predictors of musical learning success were found including increased brain activation in the auditory and motor systems during listening, the microstructure of the arcuate fasciculus, and the functional connectivity between the auditory and the motor systems. We show that "the musical brain" is a product of both the natural human neurodiversity and the training practice.Functional constipation (FCon) is a common functional gastrointestinal disorder. A considerable portion of patients with FCon is associated with anxiety/depressive status (FCAD). Previous neuroimaging studies mainly focused on patients with FCon without distinguishing FCAD from FCon patients without anxiety/depressive status (FCNAD). Differences in brain functions between these two subtypes remain unclear. Thus, we employed resting-state functional magnetic resonance imaging (RS-fMRI) and graph theory method to investigate differences in brain network connectivity and topology in 41 FCAD, 42 FCNAD, and 43 age- and gender-matched healthy controls (HCs). FCAD/FCNAD showed significantly lower normalized clustering coefficient and small-world-ness. Both groups showed altered nodal degree/efficiency mainly in the rostral anterior cingulate cortex (rACC), precentral gyrus (PreCen), supplementary motor area (SMA), and thalamus. In the FCAD group, nodal degree in the SMA was negatively correlated with difficulty of defecation, and abdominal pain was positively correlated with nodal degree/efficiency in the rACC, which had a lower within-module nodal degree. The salience network (SN) exhibited higher functional connectivity (FC) with the sensorimotor network (SMN) in FCAD/FCNAD, and FC between these two networks was negatively correlated with anxiety ratings in FCAD group. Additionally, FC of anterior insula (aINS)-rACC was only correlated with constipation symptom (i.e., abdominal pain) in the FCNAD group. In the FCAD group, FCs of dorsomedial prefrontal cortex-rACC, PreCen-aINS showed correlations with both constipation symptom (i.e., difficulty of defecation) and depressive status. These findings indicate the differences in FC of the SN-SMN between FCAD and FCNAD and provide neuroimaging evidence based on brain function, which portrays important clues for improving new treatment strategies.Advances in large-scale proteomics analysis have been very useful in understanding pathogenesis of diseases and elaborating therapeutic strategies. Proteomics has been employed to study Parkinson disease (PD); however, sparse studies reported proteome investigation after cell therapy approaches. In this study, we used liquid chromatography-tandem mass spectrometry and systems biology to identify differentially expressed proteins in a translational mouse model of PD after cell therapy. Proteins were extracted from five nigrostriatal-related brain regions of mice previously lesioned with 6-hydroxydopamine in the substantia nigra. Protein expression was compared in non-grafted brain to 1 and 7 days after intranigral grafting of E12.5 embryonic ventral mesencephalon (VM). We found a total of 277 deregulated proteins after transplantation, which are enriched for lipid metabolism, oxidative phosphorylation and PD, thus confirming that our animal model is similar to human PD and that the presence of grafted cells modulates the expression of these proteins.
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