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1.
PLoS Biol ; 17(8): e3000417, 2019 08.
Article in English | MEDLINE | ID: mdl-31469831

ABSTRACT

Threatening sounds can elicit a series of defensive behavioral reactions in animals for survival, but the underlying neural substrates are not fully understood. Here, we demonstrate a previously unexplored neural pathway in mice that projects directly from the auditory cortex (ACx) to the lateral periaqueductal gray (lPAG) and controls noise-evoked defensive behaviors. Electrophysiological recordings showed that the lPAG could be excited by a loud noise that induced an escape-like behavior. Trans-synaptic viral tracing showed that a great number of glutamatergic neurons, rather than GABAergic neurons, in the lPAG were directly innervated by those in layer V of the ACx. Activation of this pathway by optogenetic manipulations produced a behavior in mice that mimicked the noise-evoked escape, whereas inhibition of the pathway reduced this behavior. Therefore, our newly identified descending pathway is a novel neural substrate for noise-evoked escape and is involved in controlling the threat-related behavior.


Subject(s)
Auditory Cortex/physiology , Escape Reaction/physiology , Periaqueductal Gray/metabolism , Animals , Auditory Cortex/metabolism , Auditory Perception/physiology , Behavior, Animal/physiology , Defense Mechanisms , Excitatory Amino Acids/physiology , GABAergic Neurons/physiology , Male , Mice , Mice, Inbred C57BL , Neural Pathways/physiology , Optogenetics/methods , Periaqueductal Gray/physiology , Sound
2.
Neuron ; 97(2): 406-417.e4, 2018 01 17.
Article in English | MEDLINE | ID: mdl-29290554

ABSTRACT

In the mammalian brain, auditory information is known to be processed along a central ascending pathway leading to auditory cortex (AC). Whether there exist any major pathways beyond this canonical auditory neuraxis remains unclear. In awake mice, we found that auditory responses in entorhinal cortex (EC) cannot be explained by a previously proposed relay from AC based on response properties. By combining anatomical tracing and optogenetic/pharmacological manipulations, we discovered that EC received auditory input primarily from the medial septum (MS), rather than AC. A previously uncharacterized auditory pathway was then revealed: it branched from the cochlear nucleus, and via caudal pontine reticular nucleus, pontine central gray, and MS, reached EC. Neurons along this non-canonical auditory pathway responded selectively to high-intensity broadband noise, but not pure tones. Disruption of the pathway resulted in an impairment of specifically noise-cued fear conditioning. This reticular-limbic pathway may thus function in processing aversive acoustic signals.


Subject(s)
Auditory Pathways/physiology , Avoidance Learning/physiology , Conditioning, Classical/physiology , Fear/physiology , Limbic System/physiology , Septal Nuclei/physiology , Acoustic Stimulation , Animals , Auditory Cortex/physiology , Axonal Transport , Cochlear Nucleus/physiology , Cues , Entorhinal Cortex/physiology , Green Fluorescent Proteins/analysis , Mice , Noise/adverse effects , Pons/physiology , Rabies virus , Single-Cell Analysis
3.
Guang Pu Xue Yu Guang Pu Fen Xi ; 35(5): 1153-8, 2015 May.
Article in Chinese | MEDLINE | ID: mdl-26415418

ABSTRACT

The solution of ion mobility's nonlinear function coefficients α2 and α4 is the basis for achieving substance identification of High Field Asymmetric waveform Ion Mobility Spectrometry (FAIMS). Currently, nonlinear function coefficients α2 and α4 lack priors, meanwhile, existed solving results about α2 and α4 are deficient in error evaluation standard. In this article, acetone, isopropanol and 1, 2-dichlorobenzene were detected under different dispersion voltage by homemade FAIMS. In general, the spectrum peak of same sample at different dispersion voltage value is unique. Different dispersion voltage and corresponding compensation voltage value determines the value of α2 and α4. According to sample spectra at different dispersion voltage value, groups of spectral characteristics were obtained. Affirmatory number of data which were selected from multiple sets of compensation voltage value and dispersion voltage value, so that they were utilized to solved out lots of α2 and α4. Lots of factor have an effect on the accuracy of the solving results of α2 and α4, for instance, value of compensation voltage and dispersion voltage, style of fetching points of dispersion voltage, and so on. Comparing to other factors, style and amount of dispersion voltage is likely to control. By data analyzing huge amounts of α2 and α4 data, this paper explored their characteristic of distribution and correlation about them, research influence of number and method to fetch dispersion voltage detected points for error of solving results. After fitting frequency of α2 and α4, it was found that they conform to normal distribution, goodness of fitting exceed 0. 96, thus standard deviation of their distribution are able to evaluate error of solving results. In addition, a strong correlation exists between them, relevance of sample is -0. 977, -0. 968, -0. 992 respectively. With increasing of computing selected points, the corresponding error of solving results decrease. By comparing the standard deviation of method to fetch dispersion voltage detected points, found that detecting frequency in case of detecting maximum and the 70% of maximum of dispersion voltage value is lower at approximately same standard deviation, solving effect was optimized in unique fetching points style. Based on the premise of ensuring the accuracy of solving results of α2 and α4, it is obvious that reducing the frequency of detections for FAIMS effectively. It created favorable conditions for rapid field detection and precise spectral analysis.

4.
Yao Xue Xue Bao ; 48(1): 113-8, 2013 Jan.
Article in Chinese | MEDLINE | ID: mdl-23600151

ABSTRACT

A novel rapid method for detection of the illicit beta2-agonist additives in health foods and traditional Chinese patent medicines was developed with the desorption corona beam ionization mass spectrometry (DCBI-MS) technique. The DCBI conditions including temperature and sample volume were optimized according to the resulting mass spectra intensity. Matrix effect on 9 beta2-agonists additives was not significant in the proposed rapid determination procedure. All of the 9 target molecules were detected within 1 min. Quantification was achieved based on the typical fragment ion in MS2 spectra of each analyte. The method showed good linear coefficients in the range of 1-100 mg x L(-1) for all analytes. The relative deviation values were between 14.29% and 25.13%. Ten claimed antitussive and antiasthmatic health foods and traditional Chinese patent medicines from local pharmacies were analyzed. All of them were negative with the proposed DCBI-MS method. Without tedious sample pretreatments, the developed DCBI-MS is simple, rapid and sensitive for rapid qualification and semi-quantification of the illicit beta2-agonist additives in health foods and traditional Chinese patent medicines.


Subject(s)
Adrenergic beta-2 Receptor Agonists/analysis , Drugs, Chinese Herbal/chemistry , Food, Organic/analysis , Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization , Substance Abuse Detection/methods , Tandem Mass Spectrometry
5.
Zhongguo Zhong Yao Za Zhi ; 28(2): 143-6, 2003 Feb.
Article in Chinese | MEDLINE | ID: mdl-15015289

ABSTRACT

OBJECTIVE: To establish chemical pattern recognition method for the identification and evaluation of Atractylodes macrocephala. METHOD: The chemical constituents in methanol extract of 32 samples of A. macrocephala were determined by HPLC. The fingerprints were obtained and were handled by hierarchical clustering analysis and stepwise discriminant analysis. RESULT AND CONCLUSION: According to the result of classification, all samples collected were devided into three Grades--the superior, the ordinary and the fake. Chemical pattern recognition method was established. It may be of practical value for the quality control of A. macrocephala.


Subject(s)
Atractylodes/chemistry , Pattern Recognition, Automated , Plants, Medicinal/chemistry , Chromatography, High Pressure Liquid/methods , Cluster Analysis , Quality Control , Rhizome/chemistry
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