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The distribution of neuropeptide Y (NPY) Y1 receptor-like immunoreactivity (Y1R-LI) has been studied in detail in the CNS of rat using a rabbit polyclonal antibody against the C-terminal 13 amino acids of the rat receptor protein. The indirect immunofluorescence technique with tyramide signal amplification has been employed. For specificity and comparative reasons Y1 knock-out mice and wild-type controls were analyzed. The distribution of Y1R mRNA was also studied using in situ hybridization. A limited comparison between Y1R-LI and NPY-LI was carried out.A widespread and abundant distribution of Y1R-LI, predominantly in processes but also in cell bodies, was observed. In fact, Y1R-LI was found in most regions of the CNS with a similar distribution pattern between rat and wild-type mouse. This staining was specific in the sense that it was absent in adjacent sections following preadsorption of the antibody with 10−5 M of the antigenic peptide, and that it could not be observed in sections of the Y1 KO mouse. In contrast, the staining obtained with an N-terminally directed Y1R antiserum did not disappear, strongly suggesting unspecificity. In brief, very high levels of Y1R-LI were seen in the islands of Calleja, the anterior olfactory nucleus, the molecular layer of the dentate gyrus, parts of the habenula, the interpeduncular nucleus, the mammillary body, the spinal nucleus of the trigeminal, caudal part, the paratrigeminal nucleus, and superficial layers of the dorsal horn. High levels were found in most cortical areas, many thalamic nuclei, some subnuclei of the amygdaloid complex, the hypothalamus and the nucleus of the stria terminalis, the nucleus of the solitary tract, the parabrachial nucleus, and the inferior olive. Moderate levels of Y1R-LI were detected in the cornu Ammonis and the subicular complex, many septal, some thalamic and many brainstem regions. Y1R staining of processes, often fiber and/or dot-like, and occasional cell bodies was also seen in tracts, such as the lateral lemniscus, the rubrospinal tract and the spinal tract of the trigeminal. There was in general a good overlap between Y1R-LI and NPY-LI, but some exceptions were found. Thus, some areas had NPY innervation but apparently lacked Y1Rs, whereas in other regions Y1R-LI, but no or only few NPY-positive nerve endings could be detected.Our results demonstrate that NPY signalling through the Y1R is common in the rat (and mouse) CNS. Mostly the Y1R is postsynaptic but there are also presynaptic Y1Rs. Mostly there is a good match between NPY-releasing nerve endings and Y1Rs, but ‘volume transmission’ may be ‘needed’ in some regions. Finally, the importance of using proper control experiments for immunohistochemical studies on seven-transmembrane receptors is stressed. [Copyright &y& Elsevier]

• Clinical evidence indicates the key role of adipokines in amyotrophic lateral sclerosis (ALS) pathophysiology. • This study is the first meta -analysis and systematic review of case-control studies published comparing the serum levels of adipokines in ALS patients compared with control groups. • Although serum adiponectin levels were elevated in ALS patients, the association was not statistically significant, though a trend was noted in older individuals. • ALS patients exhibited significantly lower serum leptin levels compared to controls, indicating a potential role of leptin deficiency in ALS progression. • These findings suggest that targeting adipokine signaling pathways, especially leptin and ghrelin, could present new therapeutic possibilities for ALS patients. Adipokines are proposed to be associated with ALS progression through assorted pathways. Therefore, The present meta -analysis explored the link between various adipokines and ALS progression. International database like PubMed, Scopus, and Web of Science databases were searched to achieve eligible papers published before December 2023. The following PICO structure was utilized: Population (patients with ALS); Intervention (serum concentrations of ghrelin, leptin, and adiponectin), Comparison (with or without controls), and Outcome (ALS progression). the risk of bias of selected papers was assessed through the Newcastle-Ottawa Scale (NOS) tool. 11 out of 240 papers were selected for this study which were published between 2010 and 2024. Lower serum leptin concentrations were detected in the ALS compared to control groups (WMD: −0.91, 95% CI:-1.77, −0.05). Serum concentrations of adiponectin were higher in ALS compared to control groups (WMD: 0.41, 95% CI:-0.7, 0.89). Ultimately, The serum concentrations of ghrelin in the ALS groups were lower than control groups (WMD: −1.21, 95% CI: −2.95, 0.53). Our findings revealed that serum concentrations of ghrelin and leptin were higher in ALS patients compared to control, unlike adiponectin. [ABSTRACT FROM AUTHOR]

• Volitional signals for gaze control provided by multiple parallel pathways to the superior colliculus (88) • Interaction of sensory task-related signals within the multi-layered superior colliculus (79) • Convergence of bottom-up (world statistics) and top-down (goal and task) signals in the SC for gaze control (91) • Models of attention such as saliency map and their physiological basis (60) • Cerebral and subcortical inputs to control output signals for gaze in the SC (64) Volitional signals for gaze control are provided by multiple parallel pathways converging on the midbrain superior colliculus (SC), whose deeper layers output to the brainstem gaze circuits. In the first of two papers (Takahashi and Veale, 2023), we described the properties of gaze behavior of several species under both laboratory and natural conditions, as well as the current understanding of the brainstem and spinal cord circuits implementing gaze control in primate. In this paper, we review the parallel pathways by which sensory and task information reaches SC and how these sensory and task signals interact within SC's multilayered structure. This includes both bottom-up (world statistics) signals mediated by sensory cortex, association cortex, and subcortical structures, as well as top-down (goal and task) influences which arrive via either direct excitatory pathways from cerebral cortex, or via indirect basal ganglia relays resulting in inhibition or dis-inhibition as appropriate for alternative behaviors. Models of attention such as saliency maps serve as convenient frameworks to organize our understanding of both the separate computations of each neural pathway, as well as the interaction between the multiple parallel pathways influencing gaze. While the spatial interactions between gaze's neural pathways are relatively well understood, the temporal interactions between and within pathways will be an important area of future study, requiring both improved technical methods for measurement and improvement of our understanding of how temporal dynamics results in the observed spatiotemporal allocation of gaze. [ABSTRACT FROM AUTHOR]

• Female Danish Landrace pigs were anesthetized while intracranial EEG was recorded. • 18/20 subjects produced clear peak alpha frequency (PAF) using the FOOOF algorithm. • 70% of spontaneous resting-state recording time contained PAF above the 1/f-activity. • PAF was approx. normally distributed ∼ 10 Hz and robust to µECoG and penetrating electrodes. • Future studies may elucidate the mechanisms of PAF and its implication as a biomarker. The most characteristic feature of the human electroencephalogram is the peak alpha frequency (PAF). While PAF has been proposed as a biomarker in several diseases and disorders, the disease mechanisms modulating PAF, as well as its physiological substrates, remain elusive. This has partly been due to challenges related to experimental manipulation and invasive procedures in human neuroscience, as well as the scarcity of animal models where PAF is consistently present in resting-state. With the potential inclusion of PAF in clinical screening and decision-making, advancing the mechanistic understanding of PAF is warranted. In this paper, we propose the female Danish Landrace pig as a suitable animal model to probe the mechanisms of PAF and its feature as a biomarker. We show that somatosensory alpha oscillations are present in anesthetized pigs using electrocorticography and intracortical electrodes located at the sensorimotor cortex. This was evident when looking at the time-domain as well as the spectral morphology of spontaneous recordings. We applied the FOOOF-algorithm to extract the spectral characteristics and implemented a robustness threshold for any periodic component. Using this conservative threshold, PAF was present in 18/20 pigs with a normal distribution of the peak frequency between 8–12 Hz, producing similar findings to human recordings. We show that PAF was present in 69.6 % of epochs of approximately six-minute-long resting-state recordings. In sum, we propose that the pig is a suitable candidate for investigating the neural mechanisms of PAF as a biomarker for disease and disorders such as pain, neuropsychiatric disorders, and response to pharmacotherapy. [ABSTRACT FROM AUTHOR]

• The mechanism of action of RAVANS may enhance the targeting of taVNS to nucleus of the solitary tract（NTS） • RAVANS shows some therapeutic effect in chronic low back pain, depression, migraine, hypertension, cognitive impairment. • RAVANS has a potential therapeutic role in post-stroke dysphagia. • Further in-depth research is needed on the optimal parameter settings for RAVANS. Vagus nerve stimulation (VNS) has garnered significant attention as a promising bioelectronic therapy. In recent years, respiratory-gated auricular vagal afferent nerve stimulation (RAVANS), a novel non-invasive vagus nerve stimulation technique, has emerged. RAVANS integrates respiration with transcutaneous auricular vagus nerve stimulation (taVNS) and shares a similar mechanism of action to traditional VNS. Similar to conventional Vagus Nerve Stimulation (VNS), RAVANS may mitigate brain injury through three primary pathways: reducing neuronal apoptosis, modulating neurotransmitter release, and influencing inflammatory factor pathways. In this paper, we emphasize how RAVANS enhances the activation of nucleus of the solitary tract （NTS）and the locus coeruleus by regulating the monoaminergic and GABA systems through respiratory control. Additionally, it leverages the beneficial effects of respiration on the central nervous system. In this review, we delineate the potential mechanisms of action of RAVANS, provide a comprehensive overview of its clinical applications in chronic low back pain, migraine, depression, hypertension, and cognitive disorders. Furthermore, we offer future perspectives on optimizing the parameters of RAVANS and its application in post-stroke dysphagia. This will pave the way for new avenues in RAVANS research. [ABSTRACT FROM AUTHOR]

• Comprehensively synthesize the functional features of OECs. • The function and mechanism of OECs in the repair of peripheral nerve injury were discussed. • Application of OECs in the treatment of pathological pain induced by peripheral nerve injury was discussed. Direct or indirect injury of peripheral nerve can lead to sensory and motor dysfunction, which can lead to pathological pain and seriously affect the quality of life and psychosomatic health of patients. While the internal repair function of the body after peripheral nerve injury is limited. Nerve regeneration is the key factor hindering the recovery of nerve function. At present, there is no effective treatment. Therefore, more and more attention have been paid to the development of foreground treatment to achieve functional recovery after peripheral nerve injury, including relief of pathological pain. Cell transplantation strategy is a therapeutic method with development potential in recent years, which can exert endogenous alternative repair by transplanting exogenous functional bioactive cells to the site of nerve injury. Olfactory ensheathing cells (OECs) are a special kind of glial cells, which have the characteristics of continuous renewal and survival. The mechanisms of promoting nerve regeneration and functional repair and relieving pathological pain by transplantation of OECs to peripheral nerve injury include secretion of a variety of neurotrophic factors, axonal regeneration and myelination, immune regulation, anti-inflammation, neuroprotection, promotion of vascular growth and improvement of inflammatory microenvironment around nerve injury. Different studies have shown that OECs combined with biomaterials have made some progress in the treatment of peripheral nerve injury and pathological pain. These biomaterials enhance the therapeutic effect of OECs. Therefore, the functional role of OECs in peripheral nerve injury and pathological pain was discussed in this paper. Although OECs are in the primary stage of exploration in the repair of peripheral nerve injury and the application of pain, but OECs transplantation may become a prospective therapeutic strategy for the treatment of peripheral nerve injury and pathological pain. [ABSTRACT FROM AUTHOR]

[Display omitted] • This paper mainly discusses the cells based on the inflammatory mechanism to discuss their functions after ICH. • Microglia can interact with a wide range of cells, which is important for both disease development and treatment. • We believe that exploring multi-mechanism and multi-cell regulated drugs may be the future development trend. The inflammatory mechanism of intracerebral hemorrhage (ICH) has been widely studied, and it is believed that the regulation of this mechanism is of great significance to the prognosis. In the early stage of the acute phase of ICH, the release of a large number of inflammatory factors around the hematoma can recruit more inflammatory cells to infiltrate the area, further release inflammatory factors, cause an inflammatory cascade reaction, aggravate the volume of cerebral hematoma and edema and further destroy the blood–brain barrier (BBB), according to this, the crosstalk between cells may be of great significance in secondary brain injury (SBI). Because most of the cells recruited are inflammatory immune cells, this paper mainly discusses the cells based on the inflammatory mechanism to discuss their functions after ICH, we found that among the main cells inherent in the brain, glial cells account for the majority, of which microglia are the most widely studied and it can interact with a variety of cells, which is reflected in the literature researches on its pathogenesis and treatment. We believe that exploring multi-mechanism and multi-cell regulated drugs may be the future development trend, and the existing research, the comparison and unification of modeling methods, and the observation of long-term efficacy may be the first problem that researchers need to solve. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine whether a decrease in cyclic AMP accumulation mediates the inhibition of norepinephrine release in response to alpha-2 adrenergic receptor activation in cultured rat superior cervical ganglion cells. Superior cervical ganglia from neonatal rats were dissociated and cultured on collagen-coated plastic strips. Neurotransmitter release was assessed by measuring the fractional overflow of tritium in superfused cells prelabeled with [3H]norepinephrine. Intracellular cyclic AMP accumulation was measured using radioimmunoassay. Electrical field stimulation at 1 Hz, 30 pulses, 1 ms duration at 20 min intervals produced an increase in the fractional overflow of tritium that was composed predominantly of intact [3H]norepinephrine. The alpha-2 adrenergic receptor agonist UK-14,304 dose-dependently attenuated the increase in fractional tritium overflow elicited by electrical field stimulation. The adenylyl cyclase activator, forskolin, increased cyclic AMP accumulation in superior cervical ganglion cells and UK-14,304 dose-dependently inhibited forskolin-stimulated cyclic AMP accumulation. UK-14,304 had no effect on basal cyclic AMP accumulation or cyclic AMP accumulation during electrical field stimulation. Forskolin (1-10 microM) or the non-hydrolysable cAMP analog, 8-(4-chlorophenylthio)adenosine 3',5'-cyclic monophosphate (1-100 microM), slightly increased basal and dose-dependently potentiated the increase in fractional tritium overflow in response to electrical stimulation. Despite enhancement by forskolin and 8-(4-chlorophenylthio)adenosine 3',5'-cyclic monophosphate of fractional tritium overflow caused by electrical field stimulation, UK-14304 (1-10 microM) reduced release to a similar degree as that observed in the absence of forskolin or 8-(4-chlorophenylthio)adenosine 3',5'-cyclic monophosphate.(ABSTRACT TRUNCATED AT 250 WORDS)

• The high incidence of depression in cancer patients and its impact on their quality of life. • Summarizes the potential mechanisms of comorbidity between cancer and depression. • Provides discussion and analysis of potential treatments for depression. Cancer and depression are closely interrelated, particularly in patients with advanced cancer, who often present with comorbid anxiety and depression for various reasons. Recently, there has been a growing interest in the study of depression in cancer patients, with the aim of assessing the possible triggers, predictors, adverse events, and possible treatment options for depression in several common cancers. The objective of this narrative review is to synthesize the extant literature on the relationship between the occurrence and progression of depression in several common patient categories. The authors conducted a comprehensive review of 75 articles published in PubMed over the past five years. This review was further evaluated in the present paper. Ultimately, it was determined that depression is a prevalent and detrimental phenomenon among cancer patients, particularly those with advanced disease. Consequently, there is a pressing need to prioritize research and interventions aimed at improving the quality of life and psychosocial well-being of cancer patients, including those with advanced disease. The relationship between cancer and depression has been evolving dynamically in recent times. The current research findings indicate a strong association between cancer and depression. However, the direction of causality remains unclear. Focusing on depression in cancer patients may, therefore, be beneficial for these patients. [ABSTRACT FROM AUTHOR]

• The increase of decoding precision of motor imaging EEG signal. • The hybrid TCN and ViT method achieves good results. • A shared convolution strategy and a dual-branching strategy. Brain-computer interface (BCI) is a technology that directly connects signals between the human brain and a computer or other external device. Motor imagery electroencephalographic (MI-EEG) signals are considered a promising paradigm for BCI systems, with a wide range of potential applications in medical rehabilitation, human–computer interaction, and virtual reality. Accurate decoding of MI-EEG signals poses a significant challenge due to issues related to the quality of the collected EEG data and subject variability. Therefore, developing an efficient MI-EEG decoding network is crucial and warrants research. This paper proposes a loss joint training model based on the vision transformer (VIT) and the temporal convolutional network (EEG-VTTCNet) to classify MI-EEG signals. To take advantage of multiple modules together, the EEG-VTTCNet adopts a shared convolution strategy and a dual-branching strategy. The dual-branching modules perform complementary learning and jointly train shared convolutional modules with better performance. We conducted experiments on the BCI Competition IV-2a and IV-2b datasets, and the proposed network outperformed the current state-of-the-art techniques with an accuracy of 84.58% and 90.94%, respectively, for the subject-dependent mode. In addition, we used t-SNE to visualize the features extracted by the proposed network, further demonstrating the effectiveness of the feature extraction framework. We also conducted extensive ablation and hyperparameter tuning experiments to construct a robust network architecture that can be well generalized. [ABSTRACT FROM AUTHOR]

• Scientists can use social media apps to reach broad audiences with educational content. • On TikTok, only likes , shares , and viewer retention predicted the number of views videos received. • TikTok videos summarizing research papers received the highest viewer engagement. • 84% of users reported feeling more trustful of science/scientists after following. Social media has revolutionized science communication, allowing for rapid dissemination of science-related content to the public. In recent years, video platforms like TikTok and Instagram have implemented recommendation algorithms that track users' interests and suggest personalized videos. As a result, these apps have become powerful tools for public messaging, facilitating access to audiences that are naturally curious about science. In 2020 I began uploading educational science videos to TikTok which have collectively accumulated more than 48 million views and 8 million "likes." Here I present an analysis of video metrics collected from the TikTok app for a random sampling of 150 videos, searching for factors that predict the number of views a video receives and the level of viewer engagement. Videos with higher view counts were liked and shared at higher rates and sustained viewer attention for longer. Properties like hashtags, sounds, and effects did not significantly influence video views. Interestingly, videos summarizing research papers received the highest levels of engagement, potentially reflecting high demand from lay audiences who are traditionally unable to access scientific literature. Finally, I present survey data demonstrating that 84% of users report feeling more trustful of science & scientists after following this account. Although the generalizability of these findings is limited, the results offer insights into the factors that drive video performance on TikTok and how users engage with scientific content on social media. These findings may help science communicators more effectively reach wider audiences and promote science literacy in new and innovative ways. [ABSTRACT FROM AUTHOR]

• A systematic review of the pathophysiologic processes of SAH was conducted. • The role of natural compounds in the pathophysiologic process of SAH. • Signaling pathway mechanisms by which natural compounds act in SAH. • Natural compounds are categorized in detail. • Evaluate the prognostic potential of natural compounds to improve SAH. Subarachnoid hemorrhage (SAH) is a common and fatal cerebrovascular disease with high morbidity, mortality and very poor prognosis worldwide. SAH can induce a complex series of pathophysiological processes, and the main factors affecting its prognosis are early brain injury (EBI) and delayed cerebral ischemia (DCI). The pathophysiological features of EBI mainly include intense neuroinflammation, oxidative stress, neuronal cell death, mitochondrial dysfunction and brain edema, while DCI is characterized by delayed onset ischemic neurological deficits and cerebral vasospasm (CVS). Despite much exploration in people to improve the prognostic outcome of SAH, effective treatment strategies are still lacking. In recent years, numerous studies have shown that natural compounds of plant origin have unique neuro- and vascular protective effects in EBI and DCI after SAH and long-term neurological deficits, which mainly include inhibition of inflammatory response, reduction of oxidative stress, anti-apoptosis, and improvement of blood–brain barrier and cerebral vasospasm. The aim of this paper is to systematically explore the processes of neuroinflammation, oxidative stress, and apoptosis in SAH, and to summarize natural compounds as potential targets for improving the prognosis of SAH and their related mechanisms of action for future therapies. [ABSTRACT FROM AUTHOR]

• Introduced the Siamese 4D-Alznet, which combines five distinct blocks of CNNs. • We proposed three custom TL models incorporating frozen and replacing layers. • Our methods prove 95.07% binary classification performance in terms of accuracy. • All techniques performed best for NC, EMCI, LMCI, and AD classification. Alzheimer's disease (AD) is the general form of dementia, leading to a progressive neurological disorder characterized by memory loss due to brain cell damage. Artificial Intelligence (AI) assists in the early identification and prediction of AD patients, determining future risks and benefits for radiologists and doctors to save time and cost. Since deep learning (DL) approaches work well with massive datasets and have recently become helpful for AD detection, there remains an area for improvement in automating detection performance. Present approaches somehow addressed the challenges of limited annotated data samples for binary classification. This contrasts with prior state-of-the-art techniques, which were constrained by their incapacity to capture abstract-level information. In this paper, we proposed a Siamese 4D-AlzNet model comprised of four parallel convolutional neural network (CNN) streams (Five CNN layer blocks) and customized transfer learning models (Frozen VGG-19, Frozen VGG-16, and customized AlexNet). Siamese 4D-AlzNet was vertically and horizontally stored, and the spatial features were passed to the final layer for classification. For experiments, T1-weighted MRI images comprised of four distinct subject classes, normal control (NC), mild cognitive impairment (MCI), late mild cognitive impairment (LMCI), and AD, have been employed. Our proposed models achieved outstanding accuracy, with a remarkable 95.05% accuracy distinguishing between normal and AD subjects. The performance across remaining binary class pairs consistently exceeded 90%. We thoroughly compared our model with the latest methods using the same dataset as our reference. Our proposed model improved NC-AD and MCI-AD classification accuracy by 2% 7%. [ABSTRACT FROM AUTHOR]

• Friedrich Bonhoeffer and his team discovered Roger Sperry's molecular labels. • He was pioneer in developing powerful in vitro assays for axon guidance. • He showed these labels were graded, membrane bound cues in retina and targets. • Throughout the 80′s-90′s, his lab was an epicenter of scientific innovation. • The fixed tissue DiI labeling method was discovered in his lab. The main focus of research for which Friedrich Bonhoeffer's work is known in the Neuroscience community was pioneer experiments on how axonal projections could organize into "maps", what mechanisms are involved in axon guidance and involve gradients of guiding molecules, and isolation of the first such molecules, e.g. RAGS (ephrin A5) and RGM (repulsive guidance molecule). Other papers have described in detail these contributions as well as Friedrich Bonhoeffer's personality. In the mid-eighties, I made a 2-year stay in his lab and initiated a line of research on development of binocular connections in Mammals, particularly the guidance of retinal fibers to one or the other side of the brain. In this paper I recall these circumstances as they pertain to Neuroscience as it stood at the time, and explain as best as I can how his lab was a conducive setting for the discoveries made there and how Friedrich Bonhoeffer acted for me as a scientist and a tutor. [ABSTRACT FROM AUTHOR]

• We design a multi-classification scheme based on 29 electroencephalogram characters. • We use three methods for feature extraction and compare the results. • We use four classifiers for 29 classification and compare the results. • The final 29 classification accuracy using KNN and KPC is 96.2%. In the field of brain-to-text communication, it is difficult to finish highly dexterous behaviors of writing multi-character by motor-imagery-based brain–computer interface (MI-BCI), setting a barrier to restore communication in people who have lost the ability to move and speak. In this paper, we design and implement a multi-character classification scheme based on 29 characters of motor imagery (MI) electroencephalogram (EEG) signals, which contains 26 English letters and 3 punctuation marks. Firstly, we design a novel experimental paradigm to increase the variety of BCI inputs by asking subjects to imagine the movement of writing 29 characters instead of gross motor skills such as reaching or grasping. Secondly, because of the high dimension of EEG signals, we adopt power spectral density (PSD), principal components analysis (PCA), kernel principal components analysis (KPCA) respectively to decompose EEG signals and extract feature, and then test the results with pearson product-moment correlation coefficient (PCCs). Thirdly, we respectively employ k-nearest neighbor (kNN), support vector machine (SVM), extreme learning machine (ELM) and light gradient boosting machine (LightGBM) to classify 29 characters and compare the results. We have implemented a complete scheme, including paradigm design, signal acquisition, feature extraction and classification, which can effectively classify 29 characters. The experimental results show that the KPCA has the best feature extraction effect and the kNN has the highest classification accuracy, with the final classification accuracy reaching 96.2%, which is better than other studies. [ABSTRACT FROM AUTHOR]

• VNS and rhythmic field activity. • Rhythmic brain oscillations and VNS. • VNS and brain EEG field potential. More than thirty years of medical treatment with the use of vagal nerve stimulation (VNS) has shown that this therapeutic procedure works in a number of homeostatic disturbances. Although the clinical usage of VNS has a long history, our knowledge about the central mechanisms underlying this treatment is still limited. In the present paper we review the effects of VNS on brain oscillations as a possible electrophysiological bio-marker of VNS efficacy. The review was prepared mainly on the basis of data delivered from clinical observations and the outcomes of electrophysiological experiments conducted on laboratory animals that are available in PubMed. We consciously did not focus on epileptiform activity understood as a pathologic oscillatory activity, which was widely discussed in the numerous previously published reviews. The main conclusion of the present paper is that further, well-designed experiments on laboratory animals are absolutely necessary to address the electrophysiological issues. These will fill a number of gaps in our present knowledge of the central mechanisms underlying VNS therapy. [ABSTRACT FROM AUTHOR]

• NEDD4L is elevated in brain tissue of chronic mild unpredictable stress (CUMS) mice. • Inhibition of NEDD4 improves activated astrocytes and inflammation in CUMS mice. • NEDD4L binds to PAX6 (paired box 6) and promotes its ubiquitinated degradation. • PAX6 binds to P2X7R (purinergic ligand-gated ion channel 7 receptor) promoter. • Inhibition of PAX6 partially reverses the effect of NEDD4L on depression. Astrocytes are implicated in stress-induced neuroinflammatory responses in depression. This paper was to explore the molecular mechanism of the E3 ubiquitin ligase NEDD4L (NEDD4 like E3 ubiquitin protein ligase) in depressed mice by regulating astrocyte activation, and to find a new target for depression. A mouse model of depression was established by CUMS (chronic mild unpredictable stress) in 48 6-week male C57BL/6 mice and injected with sh-NEDD4L vector for testing behavioral and cognitive abilities, histopathological changes, and the number of GFAP-positive cells. The mRNA and protein levels of NEDD4L, PAX6 (paired box 6) and P2X7R (purinergic ligand-gated ion channel 7 receptor) were measured. Inflammation model was established by lipopolysaccharide treatment of mouse astrocyte line C8-D1A and infected with sh-NEDD4L. After CUMS induction, mice showed depression-like symptoms, increased inflammatory infiltration, decreased glial fibrillary acidic protein (GFAP)-positive cells in brain tissue, and increased NEDD4L protein levels. NEDD4L inhibition increased GFAP-positive cells, increased PAX6 protein levels and decreased P2X7R mRNA and protein levels, and decreased inflammatory factor secretion in brain tissue and in vitro cells. PAX6 knockdown or P2X7R overexpression partially reversed the effects of NEDD4L inhibition on astrocyte activation and neuroinflammation. To conclude, highly-expressed NEDD4L in depression-like mouse brain inhibits astrocyte activation and exacerbates neuroinflammation by ubiquitinating PAX6 and promoting P2X7R level. [ABSTRACT FROM AUTHOR]

• Mitochondria damage defines the cell death process in motoneuron degeneration. • Distal mitochondria are more susceptible to damage than perinuclear mitochondria. • The shift from apoptotic to necrotic process is controlled by mitochondria healthy population. Mitochondrial damage is a central mechanism involved in neurological disorders as Alzheimer's, and Parkinson's diseases and amyotrophic lateral sclerosis. Energy production is the most studied mitochondrial function; however, mitochondria are also involved in processes like calcium buffering homeostasis, and cell death control during apoptosis and necrosis. Using transmission electron microscopy, in this in vivo study in male rats, we describe ultrastructural mitochondrial alterations of spinal motor neurons along chronic AMPA-induced excitotoxicity, which has been described as one of the most relevant mechanisms in ALS disease. Mitochondrial alterations begin with a crest swelling, which progresses to a full mitochondrial swelling and crest disruption. Changes on the mitochondrial morphology from elongated to a circular shape also occur along the AMPA-excitotoxicity process. In addition, by combining the TUNEL assay and immunohistochemistry for mitochondrial enzymes, we show evidence of mitochondrial DNA damage. Evidence of mitochondrial alterations during an AMPA-excitotoxic event is relevant because resembles the mitochondrial alterations previously reported in ALS patients and in transgenic familial ALS models, suggesting that a chronic excitotoxic model can be related to sporadic ALS (as has been shown in recent papers), which represent more than the 90% of the ALS cases. Understanding the mechanisms involved in motor neuron degenerative process, such as the ultrastructural mitochondrial changes permits to design strategies for MN-degeneration treatments in ALS. [ABSTRACT FROM AUTHOR]

• Gut-brain axis is involve in aged-related neurological disorders like Alzheimer. • Oral and gut dysbiosis has been associated to biomarkers of cognitive decline. • Microbial-derived metabolites could modulate tau and β-amyloid deposition. • Gut microbiome could affect brain activity via epigenetic changes. • Oral and gut dysbiosis as additional hallmark of human aging and neurodegeneration. Gut microbiota represents a diverse and dynamic population of microorganisms harbouring the gastrointestinal tract, which influences host health and disease. Bacterial colonization of the gastrointestinal tract begins at birth and changes throughout life, with age being one of the conditioning factors for its vitality. Aging is also a primary risk factor for most neurodegenerative diseases. Among them, Alzheimeŕs disease (AD) is probably the one where its association with a state of dysbiosis of the gut microbiota has been most studied. In particular, intestinal microbial-derived metabolites have been associated with β-amyloid formation and brain amyloid deposition, tau phosphorylation, as well as neuroinflammation in AD patients. Moreover, it has been suggested that some oral bacteria increase the risk of developing AD. However, the causal connections among microbiome, amyloid-tau interaction, and neurodegeneration need to be addressed. This paper summarizes the emerging evidence in the literature regarding the link between the oral and gut microbiome and neurodegeneration with a focus on AD. Taxonomic features of bacteria as well as microbial functional alterations associated with AD biomarkers are the main points reviewed. Data from clinical studies as well as the link between microbiome and clinical determinants of AD are particularly emphasized. Further, relationships between gut microbiota and age-dependent epigenetic changes and other neurological disorders are also described. Together, all this evidence suggests that, in some sense, gut microbiota can be seen as an additional hallmark of human aging and neurodegeneration. [ABSTRACT FROM AUTHOR]

[Display omitted] • Type 2 Diabetes Mellitus increases the risk of dementia. • Lipocalin-2 levels may change with the progression of diabetes. • Lipocalin-2 is associated with the progression of diabetic encephalopathy. • Lipocalin-2 may be involved in inflammation and iron metabolism to affect cognition. Diabetic encephalopathy is a central nervous complication of diabetes mellitus which is characterized by cognitive impairment and structural and neurochemical abnormalities, which is easily neglected. Lipocalin-2 (LCN2) is a 25 kDa transporter in the lipocalin family that can transport small molecules, including fatty acids, iron, steroids, and lipopolysaccharides in the circulation. Recently, LCN2 has been found to be a significant regulator of insulin resistance and glucose homeostasis. Numerous studies have shown that LCN2 is connected to central nervous system abnormalities, including neuroinflammation and neurodegeneration, while the latest researches have found that LCN2 is closely related to the development of diabetic encephalopathy. Nevertheless, its precise role in the pathogenesis of diabetic encephalopathy remains to be determined. In this paper, we review recent evidence on the role of LCN2 in diabetic encephalopathy from multiple perspectives in order to decipher the impact of LCN2 in both the aetiology and treatment of diabetic encephalopathy. [ABSTRACT FROM AUTHOR]

[Display omitted] • MFB-ICSS reverses spatial memory deficits in Aβ-injected rats. • MFB-ICSS reserves ptau levels in CA1 and enthorhinal cortex in Aβ rats. • DBN levels in temporal regions are restored in MFB-ICSS treated Aβ rats. • DBN levels and behavioral afectation correlations change after MFB-ICSS. No curative or fully effective treatments are currently available for Alzheimer's disease (AD), the most common form of dementia. Electrical stimulation of deep brain areas has been proposed as a novel neuromodulatory therapeutic approach. Previous research from our lab demonstrates that intracranial self-stimulation (ICSS) targeting medial forebrain bundle (MFB) facilitates explicit and implicit learning and memory in rats with age or lesion-related memory impairment. At a molecular level, MFB-ICSS modulates the expression of plasticity and neuroprotection-related genes in memory-related brain areas. On this basis, we suggest that MFB could be a promising stimulation target for AD treatment. In this study, we aimed to assess the effects of MFB-ICSS on both explicit memory as well as the levels of neuropathological markers ptau and drebrin (DBN) in memory-related areas, in an AD rat model obtained by Aβ icv-injection. A total of 36 male rats were trained in the Morris water maze on days 26–30 after Aβ injection and tested on day 33. Results demonstrate that this Aβ model displayed spatial memory impairment in the retention test, accompanied by changes in the levels of DBN and ptau in lateral entorhinal cortex and hippocampus, resembling pathological alterations in early AD. Administration of MFB-ICSS treatment consisting of 5 post-training sessions to AD rats managed to reverse the memory deficits as well as the alteration in ptau and DBN levels. Thus, this paper reports both cognitive and molecular effects of a post-training reinforcing deep brain stimulation procedure in a sporadic AD model for the first time. [ABSTRACT FROM AUTHOR]

• The improved encoder is proposed to get the latent variables from brain activity. • The improved decoder is proposed to reconstruct the image from the latent variables. • An optimizer is designed in the improved deep generative multiview model. • An optimizer is designed in the improved deep generative multiview model. • The image reconstruction performance of the proposed model is greatly improved. Reconstructing visual stimulus images from the brain activity signals is an important research task in the field of brain decoding. Many methods of reconstructing visual stimulus images mainly focus on how to use deep learning to classify the brain activities measured by functional magnetic resonance imaging or identify visual stimulus images. Accurate reconstruction of visual stimulus images by using deep learning still remains challenging. This paper proposes an improved deep generative multiview model to further promote the accuracy of reconstructing visual stimulus images. Firstly, an encoder based on residual-in-residual dense blocks is designed to fit the deep and multiview visual features of human natural state, and extract the features of visual stimulus images. Secondly, the structure of original decoder is extended to a deeper network in the deep generative multiview model, which makes the features obtained by each deconvolution layer more distinguishable. Finally, we configure the parameters of the optimizer and compare the performance of various optimizers under different parameter values, and then the one with the best performance is chosen and adopted to the whole model. The performance evaluations conducted on two publicly available datasets demonstrate that the improved model has more accurate reconstruction effectiveness than the original deep generative multiview model. [ABSTRACT FROM AUTHOR]

• The whole cortical functional brain networks were investigated in MDD patients based on EEG-sources. • MDD caused enhanced global functional connectivity in α band. • Increased global and local clustering coefficients were both found in MDD patients in α and β bands. Studies of scalp electroencephalography (EEG) had shown altered topological organization of functional brain networks in patients with major depressive disorder (MDD). However, most previous EEG-based network analyses were performed at sensor level, while the interpretation of obtained results was not straightforward due to volume conduction effect. To reduce the impact of this defect, the whole cortical functional brain networks of MDD patients were studied during resting state based on EEG-source estimates in this paper. First, scalp EEG signals were recorded from 19 patients with MDD and 20 normal controls under resting eyes-closed state, and cortical neural signals were estimated by using sLORETA method. Then, the correntropy coefficient of wavelet packet coefficients was performed to calculate functional connectivity (FC) matrices in four different frequency bands: δ, θ, α, β, respectively. Afterwards, topological properties of brain networks were analyzed by graph theory approaches. The results showed that the global FC strength of MDD patients was significantly higher than that of healthy subjects in α band. Also, it was found that MDD patients have abnormally increased clustering coefficient and local efficiency in both α and β bands compared to normal people. Furthermore, patients with MDD exhibited increased nodal clustering coefficients in the left lingual gryus and left precuneus in α band. In addition, β band global clustering coefficient was positively correlated with the scores of depression severity. Therefore, the findings indicated the cortical functional brain networks in MDD patients were disruptions, which suggested it would be one of potential causes of depression. [ABSTRACT FROM AUTHOR]

[Display omitted] • Physiological signals from other body regions can interfere with EEG signals. • EMG and EOG artifacts are two of the most common artifacts in EEG signals. • GRU and self-attention are the state-of-art techniques for sequential data. • The model can reconstruct a clear EEG waveform with a decent SNR and RRMSE value. • The denoising algorithm can be applied to the preprocessing stage of the EEG signal. Electroencephalography (EEG) signals are nonlinear and non-stationary sequences that carry much information. However, physiological signals from other body regions may readily interfere with EEG signal capture, having a significant unfavorable influence on subsequent analysis. Therefore, signal denoising is a crucial step in EEG signal processing. This paper proposes a bidirectional gated recurrent unit (GRU) network based on a self-attention mechanism (BG-Attention) for extracting pure EEG signals from noise-contaminated EEG signals. The bidirectional GRU network can simultaneously capture past and future information while processing continuous time sequence. And by paying different levels of attention to the content of varying importance, the model can learn more significant feature of EEG signal sequences, highlighting the contribution of essential samples to denoising. The proposed model is evaluated on the EEGdenoiseNet data set. We compared the proposed model with a fully connected network (FCNN), the one-dimensional residual convolutional neural network (1D-ResCNN), and a recurrent neural network (RNN). The experimental results show that the proposed model can reconstruct a clear EEG waveform with a decent signal-to-noise ratio (SNR) and the relative root mean squared error (RRMSE) value. This study demonstrates the potential of BG-Attention in the pre-processing phase of EEG experiments, which has significant implications for medical technology and brain-computer interface (BCI) applications. [ABSTRACT FROM AUTHOR]

Is sentence structure processed by the same neural and cognitive resources that are recruited for processing word meanings, or do structure and meaning rely on distinct resources? Linguistic theorizing and much behavioral evidence suggest tight integration between lexico-semantic and syntactic representations and processing. However, most current proposals of the neural architecture of language continue to postulate a distinction between the two. One of the earlier and most cited pieces of neuroimaging evidence in favor of this dissociation comes from a paper by Dapretto and Bookheimer (1999). Using a sentence-meaning judgment task, Dapretto & Bookheimer observed two distinct peaks within the left inferior frontal gyrus (LIFG): one was more active during a lexico-semantic manipulation, and the other during a syntactic manipulation. Although the paper is highly cited, no attempt has been made, to our knowledge, to replicate the original finding. We report an fMRI study that attempts to do so. Using a combination of whole-brain, group-level ROI, and participant-specific functional ROI approaches, we fail to replicate the original dissociation. In particular, whereas parts of LIFG respond reliably more strongly during lexico-semantic than syntactic processing, no part of LIFG (including in the region defined around the peak reported by Dapretto & Bookheimer) shows the opposite pattern. We speculate that the original result was a false positive, possibly driven by a small subset of participants or items that biased a fixed-effects analysis with low power. • Is sentence structure processed by the same brain regions that are recruited for processing word meanings? • We try to replicate distinct peaks in LIFG for semantic vs. syntactic processing reported by Dapretto and Bookheimer (1999). • Parts of LIFG respond reliably more strongly during semantic than syntactic processing. • No part of LIFG (including in the region defined around the peak reported by D&B) shows the opposite pattern. • The original D&B finding is likely a false positive driven by a subset of participants/items in a fixed-effects analysis. [ABSTRACT FROM AUTHOR]