A high-density theta burst paradigm enhances the aftereffects of transcranial magnetic stimulation: Evidence from focal stimulation of rat motor cortex

Background: Theta burst stimulation (TBS) is an efficient noninvasive neuromodulation paradigm that has been widely adopted, clinically. However, the efficacy of TBS treatment remains similarly modest as conventional 10 Hz repetitive transcranial magnetic stimulation (rTMS). Objective/hypothesis: To develop a new TBS paradigm that enhances the effects of TMS administration while maintaining high time-efficiency. Methods: We describe here a new TMS paradigm, named High-Density Theta Burst Stimulation (hdTBS). This paradigm delivers up to 6 pulses per burst, as opposed to only 3 in conventional TBS, while maintaining the inter-burst interval of 200 ms (or 5 Hz) - a critical parameter in inducing long-term potentiation. This paradigm was implemented on a TMS stimulator developed in-house; its physiological effects were assessed in the motor cortex of awake rats using a rodent specific focal TMS coil. Microwire electrodes were implanted into each rat\u27s limb muscles to longitudinally record motor-evoked potential (MEP). Four different TBS paradigms (3, 4, 5 or 6 pulses per burst, 200 s per session) were tested; MEP signals were recorded immediately before (baseline) and up to 35 min post each TBS session. Results: We developed a stimulator based on a printed-circuit board strategy. The stimulator was able to deliver stable outputs of up to 6 pulses per burst. Animal experiments (n = 15) revealed significantly different aftereffects induced by the four TBS paradigms (Friedman test, p = 0.018). Post hoc analysis further revealed that, in comparison to conventional 3-pulse TBS, 5- and 6-pulse TBS enhanced the aftereffects of MEP signals by 56% and 92%, respectively, while maintaining identical time efficiency. Conclusion(s): A new stimulation paradigm is proposed, implemented and tested in the motor cortex of awake rats using a focal TMS coil developed in the lab.We observed enhanced aftereffects as assessed by MEP, with no obvious adverse effects, suggesting the translational potentials of this paradigm

LZAP Inhibits p38 MAPK (p38) Phosphorylation and Activity by Facilitating p38 Association with the Wild-Type p53 Induced Phosphatase 1 (WIP1)

LZAP (Cdk5rap3, C53) is a putative tumor suppressor that inhibits RelA, Chk1 and Chk2 and activates p53. LZAP is lost in a portion of human head and neck squamous cell carcinoma and experimental loss of LZAP expression is associated with enhanced invasion, xenograft tumor growth and angiogenesis. p38 MAPK can increase or decrease proliferation and cell death depending on cellular context. LZAP has no known enzymatic activity, implying that its biological functions are likely mediated by its protein-protein interactions. To gain further insight into LZAP activities, we searched for LZAP-associated proteins (LAPs). Here we show that the LZAP binds p38, alters p38 cellular localization, and inhibits basal and cytokine-stimulated p38 activity. Expression of LZAP inhibits p38 phosphorylation in a dose-dependent fashion while loss of LZAP enhances phosphorylation and activation with resultant phosphorylation of p38 downstream targets. Mechanistically, the ability of LZAP to alter p38 phosphorylation depended, at least partially, on the p38 phosphatase, Wip1. Expression of LZAP increased both LZAP and Wip1 binding to p38. Taken together, these data suggest that LZAP activity includes inhibition of p38 phosphorylation and activation

Patchouli Alcohol Modulates the Pregnancy X Receptor/Toll-like Receptor 4/Nuclear Factor Kappa B Axis to Suppress Osteoclastogenesis

The incidence of osteoporosis, which is primarily characterized by plethoric osteoclast (OC) formation and severe bone loss, has increased in recent years. Millions of people worldwide, especially postmenopausal women, suffer from osteoporosis. The drugs commonly used to treat osteoporosis still exist many disadvantages, but natural extracts provide options for the treatment of osteoporosis. Therefore, the identification of cost-effective natural compounds is important. Patchouli alcohol (PA), a natural compound extracted from Pogostemon cablin that exerts anti-inflammatory effects, is used as a treatment for gastroenteritis. However, no research on the use of Patchouli alcohol in osteoporosis has been reported. We found that PA dose-dependently inhibited the receptor activator of nuclear factor kappa-B ligand (RANKL)-induced formation and function of OCs without cytotoxicity. Furthermore, these inhibitory effects were reflected in the significant effect of PA on the NF-κB signaling pathway, as PA suppressed the transcription factors NFATc1 and c-Fos. We also determined that PA activated expression of the nuclear receptor pregnane X receptor (PXR) and promoted the PXR/Toll-like receptor 4 (TLR4) axis to inhibit the nuclear import of NF-κB (p50 and p65). Additionally, PA exerted therapeutic effects against osteoporosis in ovariectomized (OVX) mice, supporting the use of PA as a treatment for osteoporosis in the future

SLAM and 3D Semantic Reconstruction Based on the Fusion of Lidar and Monocular Vision

Monocular camera and Lidar are the two most commonly used sensors in unmanned vehicles. Combining the advantages of the two is the current research focus of SLAM and semantic analysis. In this paper, we propose an improved SLAM and semantic reconstruction method based on the fusion of Lidar and monocular vision. We fuse the semantic image with the low-resolution 3D Lidar point clouds and generate dense semantic depth maps. Through visual odometry, ORB feature points with depth information are selected to improve positioning accuracy. Our method uses parallel threads to aggregate 3D semantic point clouds while positioning the unmanned vehicle. Experiments are conducted on the public CityScapes and KITTI Visual Odometry datasets, and the results show that compared with the ORB-SLAM2 and DynaSLAM, our positioning error is approximately reduced by 87%; compared with the DEMO and DVL-SLAM, our positioning accuracy improves in most sequences. Our 3D reconstruction quality is better than DynSLAM and contains semantic information. The proposed method has engineering application value in the unmanned vehicles field

Comparison of Visually Evoked Local Field Potentials in Isolated Turtle Brain: Patterned Versus Blank Stimulation

Isolated turtle brain/eye preparation has recently been used as a bloodless animal model for detecting the magnetic resonance imaging (MRI) signal changes produced by visually evoked neuronal currents. The present work aims to determine whether checkerboard-patterned or full field flash (blank) stimulation should be used in order to achieve stronger neuronal responses in turtle brain/eye preparation. The knowledge gained in this study is essential for optimizing the visual stimulation methods in functional neuroimaging studies using turtle brain/eye preparation. In this study, visually evoked local field potentials (LFPs) were measured and compared in turtle visual cortex and optic tectum elicited by checkerboard and full field flash stimuli with three different inter-stimulus intervals (ISIs=5, 10, and 16s). It was found that the behavior of neuronal adaptation in the cortical and tectal LFP signals for checkerboard stimulation was comparable to flash stimulation. In addition, there was no significant difference in the LFP peak amplitudes (ISI=16s) between these two stimuli. These results indicate that the intensity of neuronal responses to checkerboard is comparable to flash stimulation. These two stimulation methods should be equivalent in functional neuroimaging studies using turtle brain/eye preparation

SLAM and 3D Semantic Reconstruction Based on the Fusion of Lidar and Monocular Vision

Monocular camera and Lidar are the two most commonly used sensors in unmanned vehicles. Combining the advantages of the two is the current research focus of SLAM and semantic analysis. In this paper, we propose an improved SLAM and semantic reconstruction method based on the fusion of Lidar and monocular vision. We fuse the semantic image with the low-resolution 3D Lidar point clouds and generate dense semantic depth maps. Through visual odometry, ORB feature points with depth information are selected to improve positioning accuracy. Our method uses parallel threads to aggregate 3D semantic point clouds while positioning the unmanned vehicle. Experiments are conducted on the public CityScapes and KITTI Visual Odometry datasets, and the results show that compared with the ORB-SLAM2 and DynaSLAM, our positioning error is approximately reduced by 87%; compared with the DEMO and DVL-SLAM, our positioning accuracy improves in most sequences. Our 3D reconstruction quality is better than DynSLAM and contains semantic information. The proposed method has engineering application value in the unmanned vehicles field

Single-Trial Evoked Potential Estimating Based on Sparse Coding under Impulsive Noise Environment

Estimating single-trial evoked potentials (EPs) corrupted by the spontaneous electroencephalogram (EEG) can be regarded as signal denoising problem. Sparse coding has significant success in signal denoising and EPs have been proven to have strong sparsity over an appropriate dictionary. In sparse coding, the noise generally is considered to be a Gaussian random process. However, some studies have shown that the background noise in EPs may present an impulsive characteristic which is far from Gaussian but suitable to be modeled by the α-stable distribution 1<α≤2. Consequently, the performances of general sparse coding will degrade or even fail. In view of this, we present a new sparse coding algorithm using p-norm optimization in single-trial EPs estimating. The algorithm can track the underlying EPs corrupted by α-stable distribution noise, trial-by-trial, without the need to estimate the α value. Simulations and experiments on human visual evoked potentials and event-related potentials are carried out to examine the performance of the proposed approach. Experimental results show that the proposed method is effective in estimating single-trial EPs under impulsive noise environment