Electromagnetic stimulation is an important neuromodulation technique that modulates the electrical activity of neurons and affects cortical excitability for the purpose of modulating the nervous system. The phenomenon of inverse stochastic resonance is a response mechanism of the biological nervous system to external signals and plays an important role in the signal processing of the nervous system. In this paper, a small-world neural network with electrical synaptic connections was constructed, and the inverse stochastic resonance of the small-world neural network under electromagnetic stimulation was investigated by analyzing the dynamics of the neural network. The results showed that: the Levy channel noise under electromagnetic stimulation could cause the occurrence of inverse stochastic resonance in small-world neural networks; the characteristic index and location parameter of the noise had significant effects on the intensity and duration of the inverse stochastic resonance in neural networks; the larger the probability of randomly adding edges and the number of nearest neighbor nodes in small-world networks, the more favorable the anti-stochastic resonance was; by adjusting the electromagnetic stimulation parameters, a dual regulation of the inverse stochastic resonance of the neural network can be achieved. The results of this study provide some theoretical support for exploring the regulation mechanism of electromagnetic nerve stimulation technology and the signal processing mechanism of nervous system.
Action Potentials/physiology* ; Computer Simulation ; Models, Neurological ; Stochastic Processes ; Neurons/physiology* ; Electromagnetic Phenomena

BACKGROUNDTertiary hospitals serve as the medical service center within the region and play an important role in the medical and health service system. They are also the key targets of public hospital reform in the new era in China. Through the reform of health system, the public hospital efficiency has changed remarkably. Therefore, this study aimed to provide some advice for efficiency assessment of public hospitals in China by comparing and analyzing the consistency of results obtained by three commonly used methods for examining hospital efficiency, that is, ratio analysis (RA), stochastic frontier analysis (SFA), and data envelopment analysis (DEA).

METHODSThe theoretical basis, operational processes, and the application status of RA, SFA, and DEA were learned through literature analysis. Then, the empirical analysis was conducted based on measured data from 51 tertiary public hospitals in Beijing from 2009 to 2011.

RESULTSThe average values of hospital efficiency calculated by SFA with index screening and principal component analysis (PCA) results and those calculated by DEA with index screening results were relatively stable. The efficiency of specialized hospitals was higher than that of general hospitals and that of traditional Chinese medicine hospitals. The results obtained by SFA with index screening results and the results obtained by SFA with PCA results showed a relatively high correlation (r-value in 2009, 2010, and 2011 were 0.869, 0.753, and 0.842, respectively, P < 0.01). The correlation between results obtained by DEA with index screening results and PCA results and results obtained by other methods showed statistical significance, but the correlation between results obtained by DEA with index screening results and PCA results was lower than that between results obtained by SFA with index screening results and PCA results.

CONCLUSIONSRA is not suitable for multi-index evaluation of hospital efficiency. In the given conditions, SFA is a stable efficiency analysis method. In the evaluation of hospital efficiency, DEA combined with PCA should be adopted with caution due to its poor stability.

The somatic epigenome can be reprogrammed to a pluripotent state by a combination of transcription factors. Altering cell fate involves transcription factors cooperation, epigenetic reconfiguration, such as DNA methylation and histone modification, posttranscriptional regulation by microRNAs, and so on. Nevertheless, such reprogramming is inefficient. Evidence suggests that during the early stage of reprogramming, the process is stochastic, but by the late stage, it is deterministic. In addition to conventional reprogramming methods, dozens of small molecules have been identified that can functionally replace reprogramming factors and significantly improve induced pluripotent stem cell (iPSC) reprogramming. Indeed, iPS cells have been created recently using chemical compounds only. iPSCs are thought to display subtle genetic and epigenetic variability; this variability is not random, but occurs at hotspots across the genome. Here we discuss the progress and current perspectives in the field. Research into the reprogramming process today will pave the way for great advances in regenerative medicine in the future.
Animals ; Cell Differentiation ; Cellular Reprogramming ; MicroRNAs ; genetics ; Models, Biological ; Pluripotent Stem Cells ; cytology ; metabolism ; Stochastic Processes

The on-site labeling and localization tracking of membrane proteins in pathogenic bacteria are tedious work. In order to develop a novel protein labeling technology at super resolution level (nanometer scale) using the photoactivatable localization microscopy (PALM), the chimeric protein of the outer membrane protein A (OmpA) of Mycobacterium tuberculosis and the photoactivatable mEos2m protein were expressed in the non-pathogenic Mycobacterium smegmatis. The recombinant bacteria were fixed on slide, activated by 405 nm laser and subject to PALM imaging to capture photons released by the fusion protein. Meanwhile, colony and cell morphology were visualized under regular fluorescent stereomicroscope and upright fluorescent microscope to characterize fluorescence conversion and protein localization. The fusion proteins formed a "belt"-like structure on cell membrane of M. smegmatis under PALM, providing direct evidence of on-site imaging of membrane proteins. Expression of fusion protein did not compromise the localization properties of OmpA. Thus, mEos2m could be used as a labeling probe to track localizations of non-oligomer oriented membrane proteins. This indicates non-pathogenic M. smegmatis could be served as a model strain to characterize the function and localization of the proteins derived from pathogenic M. tuberculosis. This is the first report using PALM to characterize localization of membrane proteins.
Bacterial Outer Membrane Proteins ; analysis ; chemistry ; Fluorescent Dyes ; Light ; Microscopy ; methods ; Mycobacterium smegmatis ; chemistry ; Mycobacterium tuberculosis ; chemistry ; Nanotechnology ; methods ; Staining and Labeling ; methods ; Stochastic Processes

Cross-modal stochastic resonance is a ubiquitous phenomenon, that is, a weak signal from one sensory pathway can be enhanced by the noise from a different sensory pathway. It is a special multisensory integration (MI) that can not be explained by the inverse-effectiveness rule. According to cross-modal stochastic resonance, the detection of signal is an inverted U-like function of the intensity of noise at different levels. In this paper, we reviewed the research of cross-modal stochastic resonance and put forward some possible explanations for it. These efforts raise a new idea for neural encoding and information processing of the brain.
Acoustic Stimulation ; Auditory Perception ; physiology ; Brain ; physiology ; Humans ; Mental Processes ; physiology ; Sensory Thresholds ; physiology ; Stochastic Processes ; Visual Perception ; physiology

Bursting is an important firing mode of neurons. To propose a stochastic model of bursting spike train, the interspike interval (ISI) characteristics of single-spiking train and bursting spike train were analyzed and compared. In contrast with the exponential distribution of ISI in single-spiking train, normal distribution is supposed to be the ISI model of bursting spike train. Simulated neural spike trains were produced to investigate the spectrum features of the ISI model. The results showed that: (1) bursting spike train with normally distributed ISI held a low-pass spectrum while the spectrum of single-spiking train was flat; (2) the coefficient of variation of ISI in bursting train decided the bandwidth of its low-pass spectrum. Then neural activities from anesthetized rodent were used to check the validity of the model. 10 simultaneously recorded bursting spike trains and 10 single-spiking trains were selected during anesthesia and after pure-oxygen-washout period respectively. The spectrograms of these neural spike trains were analyzed and the results were matched with our mathematical model. It is believed that the bursting spike train model established in this paper will help to theoretically study the statistical characters of neural spike train and to add mathematical foundation in neural coding schemes.
Action Potentials ; physiology ; Animals ; Computer Simulation ; Electroencephalography ; Humans ; Male ; Models, Neurological ; Models, Theoretical ; Neurons ; physiology ; Periodicity ; Poisson Distribution ; Rats ; Rats, Wistar ; Spectrum Analysis ; Stochastic Processes

We have investigated the effects of high frequency (HF) signal on firing activity in a biologically realistic system--the noisy Hodgkin-Huxley (HH) neuron model via numerical simulations. The results show that when the HF amplitude to frequency ratio (AFR) increases, the firing rate is diminished and stochastic resonance disappears, even the HH neuron model is processing a stimulus of its most sensitive frequency. When the noise intensity is strong, the vibration resonance can be observed. Moreover, the fluctuation around the resting potential will be replaced by an oscillation of the same high frequency with the increasing AFR. The inhibition of the firing activity is consistent with the results of experiment in vivo that HF current can stop the transmission of action potential in peripheral nerve. This study is of functional significance to the biomedical research on the damages caused by electro-pollution in vivo and signal processing.
Action Potentials ; Artifacts ; Computer Simulation ; Humans ; Models, Neurological ; Neurons ; physiology ; Stochastic Processes

Based on a nonlinear neuron model, the Poisson noise is used to imitate the noisy environments of neurons, and, further, the phenomenon of coherence resonance (CR) of a nonlinear neuron model subject to a voltage-gated channel noise and a random point trains synaptic noise is investigated. Based on the fractional noise theory and Euler schemes, the evolution of the membrane potential and the coefficient of variation (CV) of the interval-spike-interval of the neuron firing have been obtained. It is shown that, in the absence of external periodic signal, such CV can be decreased at a certain intensity of neurotransmitter arrivals trains lambda and a proper strength of the voltage-gated channel noise D, so that the coherence of the system is maximal and the phenomenon of CR can take place.
Action Potentials ; physiology ; Cerebral Cortex ; cytology ; physiology ; Computer Simulation ; Humans ; Models, Neurological ; Neurons ; cytology ; physiology ; Poisson Distribution ; Stochastic Processes ; Synapses ; physiology

In nonlinear systems, noise can improve the responses of the systems with appropriate noise intensity. This phenomenon is called stochastic resonance. Biological neural systems are noisy and stochastic resonance has been found in them experimentally and theoretically. Now many researches focus on the signal transmission and processing in neural models. So this paper introduces the researches of stochastic resonance in noisy neural models. Then the recent research achievement and progress are reviewed in the following three aspects: noise; the development of stochastic resonance; and neural network. At last, the foreground of the study is discussed.
Humans ; Models, Neurological ; Neurons ; physiology ; Nonlinear Dynamics ; Signal Transduction ; Stochastic Processes

Chaos and fractals are ubiquitous phenomena of nature. A system with fractal structure usually behaves chaos. As a complicated nonlinear dynamics system, heart has fractals structure and behaves as chaos. The deeper inherent mechanism of heart can be opened out when the chaos and fractals theory is utilized in the research of the electrical activity of heart. Generally a time series of a system was used for describing the status of the strange attractor of the system. The indices include Poincare plot, fractals dimension, Lyapunov exponent, entropy, scaling exponent, Hurst index and so on. In this article, the basic concepts and the methods of chaos and fractals were introduced firstly. Then the applications of chaos and fractals theories in the study of electrocardial signal were expounded with example of how they are used for ventricular fibrillation.
Electrocardiography ; methods ; Fractals ; Humans ; Nonlinear Dynamics ; Signal Processing, Computer-Assisted ; Stochastic Processes