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Technological advancements in electronics and micromachining now allow the development of discrete wireless brain implantable micro-devices. Applications of such devices include stimulation or sensing and could enable direct placement near regions of interest within the brain without the need for electrode leads or separate battery compartments that are at increased risk of breakage and infection. Clinical use of leadless brain implants is accompanied by novel risks, such as migration of the implant. Additionally, the encapsulation material of the implants plays an important role in mitigating unwanted tissue reactions. These risks have the potential to cause harm or reduce the service of life of the implant. selleck compound In the present study, we have assessed post-implantation tissue reaction and migration of borosilicate glass-encapsulated micro-implants within the cortex of the brain. Twenty borosilicate glass-encapsulated devices (2 × 3.5 × 20 mm) were implanted into the parenchyma of 10 sheep for 6 months. Radiographs were taken directly post-surgery and at 3 and 6 months. Subsequently, sheep were euthanized, and GFAP and IBA-1 histological analysis was performed. The migration of the implants was tracked by reference to two stainless steel screws placed in the skull. We found no significant difference in fluoroscopy intensity of GFAP and a small difference in IBA-1 between implanted tissue and control. There was no glial scar formation found at the site of the implant's track wall. Furthermore, we observed movement of up to 4.6 mm in a subset of implants in the first 3 months of implantation and no movement in any implant during the 3-6-month period of implantation. Subsequent histological analysis revealed no evidence of a migration track or tissue damage. We conclude that the implantation of this discrete micro-implant within the brain does not present additional risk due to migration.18F-FDG positron emission tomography (PET) imaging of brain glucose use and amyloid accumulation is a research criteria for Alzheimer's disease (AD) diagnosis. Several PET studies have shown widespread metabolic deficits in the frontal cortex for AD patients. Therefore, studying frontal cortex changes is of great importance for AD research. This paper aims to segment frontal cortex from brain PET imaging using deep neural networks. The learning framework called Frontal cortex Segmentation model of brain PET imaging (FSPET) is proposed to tackle this problem. It combines the anatomical prior to frontal cortex into the segmentation model, which is based on conditional generative adversarial network and convolutional auto-encoder. The FSPET method is evaluated on a dataset of 30 brain PET imaging with ground truth annotated by a radiologist. Results that outperform other baselines demonstrate the effectiveness of the FSPET framework.Naturalistic functional magnetic resonance imaging (NfMRI) has become an effective tool to study brain functional activities in real-life context, which reduces the anxiety or boredom due to difficult or repetitive tasks and avoids the problem of unreliable collection of brain activity caused by the subjects' microsleeps during resting state. Recent studies have made efforts on characterizing the brain's hierarchical organizations from fMRI data by various deep learning models. However, most of those models have ignored the properties of group-wise consistency and inter-subject difference in brain function under naturalistic paradigm. Another critical issue is how to determine the optimal neural architecture of deep learning models, as manual design of neural architecture is time-consuming and less reliable. To tackle these problems, we proposed a two-stage deep belief network (DBN) with neural architecture search (NAS) combined framework (two-stage NAS-DBN) to model both the group-consistent and individual-specific naturalistic functional brain networks (FBNs), which reflected the hierarchical organization of brain function and the nature of brain functional activities under naturalistic paradigm. Moreover, the test-retest reliability and spatial overlap rate of the FBNs identified by our model reveal better performance than that of widely used traditional methods. In general, our model provides a promising method for characterizing hierarchical spatiotemporal features under the natural paradigm.Introduction Symptomatic carotid disease conveys a high risk of recurrent stroke. Plaque morphology and specific plaque characteristics are associated with the risk of stroke. This study aimed to evaluate the detailed plaque features by optical coherence tomography (OCT) and develop a simple scale combining clinical indicators, digital subtraction angiography (DSA), and OCT imaging markers to identify symptomatic carotid plaque. Methods Carotid plaques from consecutive patients who underwent carotid OCT imaging between June 2017 and June 2021 were evaluated. Clinical characteristics, DSA, and OCT data were compared between the symptomatic and asymptomatic groups. Logistic regression was performed to identify the factors associated with symptomatic carotid plaque and to develop a scale. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of the scale. Results A total of 90 carotid plaques from 90 patients were included (symptomatic 35.6%, asymptomatic 64.4%). Three main factors were found to be associated with symptomatic carotid plaque high-density lipoprotein cholesterol (HDL-C) less then 0.925 mmol/L (OR, 4.708; 95% CI, 1.640 to 13.517; P = 0.004), irregular plaque (OR, 4.017; 95% CI, 1.250 to 12.910; P = 0.020), and white thrombus (OR, 4.594; 95% CI, 1.141 to 18.487; P = 0.032). The corresponding score of three items produced a scale with good discrimination (AUC, 0.768; 95% CI, 0.665 to 0.871). The optimal cutoff value of the scale was 1.5 points with 59.4% sensitivity and 84.5% specificity. Conclusion The three-item scale comprising HDL-C less then 0.925 mmol/L, angiographical irregular plaque, and white thrombus detected by OCT may provide information to identify symptomatic carotid plaque. Further large-scale studies are required to validate whether the symptomatic carotid plaque scale is clinically valuable in recognizing carotid atherosclerosis in the early stages.The Dmrt genes encode the transcription factor containing the DM (doublesex and mab-3) domain, an intertwined zinc finger-like DNA binding module. While Dmrt genes are mainly involved in the sexual development of various species, recent studies have revealed that Dmrt genes, which belong to the DmrtA subfamily, are differentially expressed in the embryonic brain and spinal cord and are essential for the development of the central nervous system. Herein, we summarize recent studies that reveal the multiple functions of the Dmrt genes in various aspects of vertebrate neural development, including brain patterning, neurogenesis, and the specification of neurons.Restoring sensory circuit function after spinal cord injury (SCI) is essential for recovery of movement, yet current interventions predominantly target motor pathways. Integrated cortical sensorimotor networks, disrupted by SCI, are critical for perceiving, shaping, and executing movement. Corticocortical connections between primary sensory (S1) and motor (M1) cortices are critical loci of functional plasticity in response to learning and injury. Following SCI, in the motor cortex, corticocortical circuits undergo dynamic remodeling; however, it remains unknown how rehabilitation shapes the plasticity of S1-M1 networks or how these changes may impact recovery of movement.The cerebellar cortex is highly compartmentalized and serves as a remarkable model for pattern formation throughout the brain. In brief, the adult cerebellar cortex is subdivided into five anteroposterior units-transverse zones-and subsequently, each zone is divided into ∼20 parasagittal stripes. Zone-and-stripe pattern formation involves the interplay of two parallel developmental pathways-one for inhibitory neurons, the second for excitatory. In the inhibitory pathway, progenitor cells of the 4th ventricle generate the Purkinje cells and inhibitory interneurons. In the excitatory pathway, progenitor cells in the upper rhombic lip give rise to the external granular layer, and subsequently to the granular layer of the adult. Both the excitatory and inhibitory developmental pathways are spatially patterned and the interactions of the two generate the complex topography of the adult. This review briefly describes the cellular and molecular mechanisms that underly zone-and-stripe development with a particular focus on mutations known to interfere with normal cerebellar development and the light they cast on the mechanisms of pattern formation.The use of adjuvant corticosteroids with surgery for chronic subdural hematoma (CSDH) has received considerable attention in recent years. However, there is no conclusive evidence regarding its effectiveness and safety for CSDH. Therefore, we performed a meta-analysis and systematic review to evaluate the effectiveness and safety of corticosteroids as an adjuvant treatment for the treatment of CSDH. We comprehensively searched electronic databases (PubMed, EMBASE, Cochrane Library, and Web of Science) to identify relevant trials that investigated the efficacy and safety of adjuvant corticosteroids with surgery for CSDH, published from inception until May 2021. Outcome measures included recurrence rate, all-cause mortality, good functional outcome, length of hospitalization, and adverse events. We used the Cochrane risk of bias method to evaluate the quality of randomized controlled trials (RCTs), and the Newcastle Ottawa Scale to evaluate the quality of observational studies. We included nine studies, consisttients. Further high-quality RCTs are required to confirm the efficacy and safety of adjuvant corticosteroids in the treatment of CSDH patients.Introduction Preservation of language functioning in patients undergoing brain tumor surgery is essential because language impairments negatively impact the quality of life. Brain tumor patients have alterations in functional connectivity (FC), the extent to which brain areas functionally interact. We studied FC networks in relation to language functioning in glioma and meningioma patients. Method Patients with a low-grade glioma (N = 15) or meningioma (N = 10) infiltrating into/pressing on the language-dominant hemisphere underwent extensive language testing before and 1 year after surgery. Resting-state EEG was registered preoperatively, postoperatively (glioma patients only), and once in healthy individuals. After analyzing FC in theta and alpha frequency bands, weighted networks and Minimum Spanning Trees were quantified by various network measures. Results Pre-operative FC network characteristics did not differ between glioma patients and healthy individuals. However, hub presence and higher local and global FC are associated with poorer language functioning before surgery in glioma patients and predict worse language performance at 1 year after surgery. For meningioma patients, a greater small worldness was related to worse language performance and hub presence; better average clustering and global integration were predictive of worse outcome on language function 1 year after surgery. The average eccentricity, diameter and tree hierarchy seem to be the network metrics with the more pronounced relation to language performance. Discussion In this exploratory study, we demonstrated that preoperative FC networks are informative for pre- and postoperative language functioning in glioma patients and to a lesser extent in meningioma patients.