Electroacupuncture Zusanli (ST36) Relieves Somatic Pain in Colitis Rats by Inhibiting Dorsal Root Ganglion Sympathetic-Sensory Coupling and Neurogenic Inflammation.

Referred somatic pain triggered by hyperalgesia is common in patients with inflammatory bowel disease (IBD). It was reported that sprouting of sympathetic nerve fibers into the dorsal root ganglion (DGR) and neurogenic inflammation were related to neuropathic pain, the excitability of neurons, and afferents. The purpose of the study was to explore the potential and mechanism of electroacupuncture (EA) at Zusanli (ST36) for the intervention of colon inflammation and hyperalgesia. Sprague-Dawley (SD) was randomly divided into four groups, including control, model, EA, and sham-EA. Our results showed EA treatment significantly attenuated dextran sulfate sodium- (DSS-) induced colorectal lesions and inflammatory cytokine secretion, such as TNF-α, IL-1ß, PGE2, and IL-6. EA also inhibited mechanical and thermal pain hypersensitivities of colitis rats. Importantly, EA effectively abrogated the promotion effect of DSS on ipsilateral lumbar 6 (L6) DRG sympathetic-sensory coupling, manifested as the sprouting of tyrosine hydroxylase- (TH-) positive sympathetic fibers into sensory neurons and colocalization of and calcitonin gene-related peptide (CGRP). Furthermore, EA at Zusanli (ST36) activated neurogenic inflammation, characterized by decreased expression of substance P (SP), hyaluronic acid (HA), bradykinin (BK), and prostacyclin (PGI2) in colitis rat skin tissues corresponding to the L6 DRG. Mechanically, EA treatment reduced the activation of the TRPV1/CGRP, ERK, and TLR4 signaling pathways in L6 DRG of colitis rats. Taken together, we presumed that EA treatment improved colon inflammation and hyperalgesia, potentially by suppressing the sprouting of sympathetic nerve fibers into the L6 DGR and neurogenic inflammation via deactivating the TRPV1/CGRP, ERK, and TLR4 signaling pathways.

Adsorbed hollow fiber immobilized tyrosinase for the screening of enzyme inhibitors from Pueraria lobata extract.

In this study, a method based on adsorbed hollow fiber immobilized tyrosinase (TYR) was developed to screening potential TYR inhibitors from Pueraria lobate extract. Kojic acid and ranitidine were used as positive and negative control to verify the reliability of the proposed method, respectively. Several significant parameters of the screening process, including the amount of P. lobata extract, adsorption time and incubation time, were optimized. After investigating the repeatability of the developed method, seven potential active compounds in P. lobata extract were successfully detected and their chemical structures were tentatively identified by liquid chromatography - mass spectrometry analysis. Furthermore, the inhibitory activity of four identified compounds on TYR was tested in vitro, and three of them, namely, puerarin, puerarin-6″-O-xyloside and puerarin apioside were verified to have good TYR inhibitory activity with IC50 value of 478.5, 513.8, and 877.3 µM, respectively. In addition, the molecular docking results indicated that these compounds could bind to the amino acid residues in TYR catalytic pocket. These results proved that the proposed method is a feasible approach for screening of TYR inhibitors from plant extract.

Antithrombotic effect and action mechanism of Salvia miltiorrhiza and Panax notoginseng herbal pair on the zebrafish.

BACKGROUND: Salvia miltiorrhiza (Danshen, DS) and Panax notoginseng (Sanqi, SQ) are famous traditional Chinese herbs, and their herbal pair (DS-SQ) has been popular used as anti-thrombotic medicines. However, there is still a lack of sufficient scientific evidence to illustrate the optimum combination ratio of these two herbs as well as its action mechanisms. The purpose of this study is to investigate the anti-thrombotic effects of DS-SQ on zebrafish and explore its possible action mechanism. METHODS: Firstly, the chemical components in DS-SQ extract were analyzed by LC-ESI-MS/MS. Then, a phenylhydrazine (PHZ)-induced zebrafish thrombosis model was developed for evaluating the anti-thrombotic effects of DS-SQ extracts with different combination ratios and their nine pure compounds. Followed, Real-time quantitative PCR (RT-qPCR) assays were performed to investigate the potential antithrombotic mechanisms of DS-SQ. RESULTS: Thirty-three components were tentatively identified by LC-MS analysis. DS-SQ at the ratio of 10:1 presented the best anti-thrombotic effect, and rosmarinic acid, lithospermic acid and salvianolic acid B of DS showed good anti-thrombotic activity on zebrafish thrombosis model. The RT-qPCR assays indicated that DS-SQ (10:1) could cure the PHZ-induced thrombosis by downregulating the expression of PKCα, PKCß, fga, fgb, fgg and vWF in zebrafish. CONCLUSIONS: DS-SQ with the combination ratio of 10:1 showed optimum anti-thrombotic effect on PHZ-induced zebrafish thrombosis model, which provided a reference for reasonable clinical applications of DS-SQ herbal pair.

Design and validation of a fully implantable, chronic, closed-loop neuromodulation device with concurrent sensing and stimulation.

Chronically implantable, closed-loop neuromodulation devices with concurrent sensing and stimulation hold promise for better understanding the nervous system and improving therapies for neurological disease. Concurrent sensing and stimulation are needed to maximize usable neural data, minimize time delays for closed-loop actuation, and investigate the instantaneous response to stimulation. Current systems lack concurrent sensing and stimulation primarily because of stimulation interference to neural signals of interest. While careful design of high performance amplifiers has proved useful to reduce disturbances in the system, stimulation continues to contaminate neural sensing due to biological effects like tissue-electrode impedance mismatch and constraints on stimulation parameters needed to deliver therapy. In this work we describe systematic methods to mitigate the effect of stimulation through a combination of sensing hardware, stimulation parameter selection, and classification algorithms that counter residual stimulation disturbances. To validate these methods we implemented and tested a completely implantable system for over one year in a large animal model of epilepsy. The system proved capable of measuring and detecting seizure activity in the hippocampus both during and after stimulation. Furthermore, we demonstrate an embedded algorithm that actuates neural modulation in response to seizure detection during stimulation, validating the capability to detect bioelectrical markers in the presence of therapy and titrate it appropriately. The capability to detect neural states in the presence of stimulation and optimally titrate therapy is a key innovation required for generalizing closed-loop neural systems for multiple disease states.

Emerging technology for advancing the treatment of epilepsy using a dynamic control framework.

We briefly describe a dynamic control system framework for neuromodulation for epilepsy, with an emphasis on its practical challenges and the preliminary validation of key prototype technologies in a chronic animal model. The current state of neuromodulation can be viewed as a classical dynamic control framework such that the nervous system is the classical "plant", the neural stimulator is the controller/actuator, clinical observation, patient diaries and/or measured bio-markers are the sensor, and clinical judgment applied to these sensor inputs forms the state estimator. Technology can potentially address two main factors contributing to the performance limitations of existing systems: "observability," the ability to observe the state of the system from output measurements, and "controllability," the ability to drive the system to a desired state. In addition to improving sensors and actuator performance, methods and tools to better understand disease state dynamics and state estimation are also critical for improving therapy outcomes. We describe our preliminary validation of key "observability" and "controllability" technology blocks using an implanted research tool in an epilepsy disease model. This model allows for testing the key emerging technologies in a representative neural network of therapeutic importance. In the future, we believe these technologies might enable both first principles understanding of neural network behavior for optimizing therapy design, and provide a practical pathway towards clinical translation.

An implantable bi-directional brain-machine interface system for chronic neuroprosthesis research.

An implantable bi-directional brain-machine interface (BMI) prototype is presented. With sensing, algorithm, wireless telemetry, and stimulation therapy capabilities, the system is designed for chronic studies exploring closed-loop and diagnostic opportunities for neuroprosthetics. In particular, we hope to enable fundamental chronic research into the physiology of neurological disorders, define key electrical biomarkers related to disease, and apply this learning to patient-specific algorithms for therapeutic stimulation and diagnostics. The ultimate goal is to provide practical neuroprosthetics with adaptive therapy for improved efficiency and efficacy.