Recently a COVID-19 pneumonia pandemic caused by a novel coronavirus 2019-nCoV has broken out over the world. In order to better control the spread of the pandemic, there’s an urgent need to extensively study the virus’ origin and the mechanisms for its infectivity and pathogenicity. Spike protein is a special structural protein on the surface of coronavirus. It contains important information about the evolution of the virus and plays critical roles in the processes of cellular recognition and entry. In the past decades, spike protein has always been one of the most important objects in research works on coronaviruses closely related to human life. In this review we introduce these research works related to spike proteins, hoping it will provide reasonable ideas for the control of the current pandemic, as well as for the diagnosis and treatment of COVID-19.
ObjectiveTo analyze the risk factors for electrical status epilepticus during sleep (ESES) in patients with self-limited epilepsy with centrotemporal spikes (SeLECTs) and to construct a nomogram model. MethodsThis study selected 174 children with SeLECTs who visited the Third Affiliated Hospital of Zhengzhou University from March 2017 to March 2024 and had complete case data as the research subjects. According to the results of video electroencephalogram monitoring during the course of the disease, the children were divided into non-ESES group (88 cases) and ESES group (86 cases). Multivariate logistic regression analysis was used to identify the risk factors for the occurrence of ESES in SeLECTs patients. ResultsThe multifactor Logistic regression analysis demonstrated that the EEG discharges in bilateral cerebral areas,types of seizure, epileptic seizures after initial treatment were the independent risk factors for the occurrence of ESES in SeLECTs. ConclusionBilateral distribution of electroencephalogram discharges before treatment, emergence of new seizure forms, and epileptic seizures after initial treatment are risk factors for the ESES in SeLECTs patients. The nomogram model constructed based on the above risk factors has a high degree of accuracy.
The measurement of network is one of the important researches in resolving neuronal population information processing mechanism using complex network theory. For the quantitative measurement problem of functional neural network, the relation between the measure indexes, i.e. the clustering coefficient, the global efficiency, the characteristic path length and the transitivity, and the network topology was analyzed. Then, the spike-based functional neural network was established and the simulation results showed that the measured network could represent the original neural connections among neurons. On the basis of the former work, the coding of functional neural network in nidopallium caudolaterale (NCL) about pigeon's motion behaviors was studied. We found that the NCL functional neural network effectively encoded the motion behaviors of the pigeon, and there were significant differences in four indexes among the left-turning, the forward and the right-turning. Overall, the establishment method of spike-based functional neural network is available and it is an effective tool to parse the brain information processing mechanism.
ObjectiveThe aim of this study is to identify clinical and electroencephalographic features associated with refractoriness to the initial antiepileptic drug in typical benign childhood epilepsy with centrotemporal spikes (BECTS). MethodsA total of 87 children with typical BECTS were retrospectively reviewed in the analyses.The patients were subdivided into two groups:patients whose seizures were controlled with monotherapy, and those requiring two medications. 63 childrenachieved seizure-freedom with monotherapy, while 24 received two medications for seizure control. ResultsDiffusing foci at the follow-up EEG and delayed treatment (duration > 1 year) are two main risk factors associated with more refractory cases (P < 0.001). Delayed diagnosis (37.1%) and non-adherence to treatment (57.2%) contributed to delayed treatment. ConclusionsOur findings suggested that diffusing foci on EEG and delayed treatment are associated with more frequent seizures and refractoriness in BECTS. Diagnostic delays and non-adherence hindered timely care, which may represent opportunities for improved intervention.
Transcranial magneto-acoustical stimulation (TMAS), utilizing focused ultrasound and a magnetostatic field to generate an electric current in tissue fluid to regulate the activities of neurons, has high spatial resolution and penetration depth. The neuronal spike-frequency adaptation plays an important role in the treatment of neural information. In this paper, we study the effects of ultrasonic intensity, magnetostatic field intensity and ultrasonic frequency on the neuronal spike-frequency adaptation based on the Ermentrout neuron model. The simulation results show that, the peak time interval becomes smaller, the interspike interval becomes shorter and the time of the firing of the neuron is shortened with the increasing of the magnetostatic field intensity. With the increase of the adaptive variables, the initial spike-frequency is shifted to the right with the magnetostatic field intensity, and the spike-frequency is linearly related to the increase of the magnetostatic field intensity in steady state. The simulation effect with change of the ultrasonic intensity is consistent with the change of magnetostatic field intensity. The change of the ultrasonic frequency has no effect on the neuronal spike-frequency adaptation. Under the different adaptive variables, with the increase of the adaptive variables, the initial spike-frequency amplitude decreased with the increasing of the ultrasonic frequency, and the spike-frequency is linearly related to the increase of the ultrasonic frequency in steady state. These results of the study can help us to reveal the mechanism of transcranial magneto-acoustical stimulation on the neuronal spike-frequency adaptation, and provide a theoretical basis for its application in the treatment of neurological disorders.
A novel coronavirus (SARS-CoV-2) that broke out at the end of 2019 is a newly discovered highly pathogenic human coronavirus and has some similarities with severe acute respiratory syndrome coronavirus (SARS-CoV). Angiotensin-converting enzyme 2 (ACE2) is the receptor for infected cells by SARS-CoV. SARS-CoV can invade cells by binding to ACE2 through the spike protein and SARS-CoV-2 may also infect cells through ACE2. Meanwhile, ACE2 also plays an important role in the course of pneumonia. Therefore the possible role of ACE2 in SARS and coronavirus disease 2019 (COVID-19) is worth discussing. This paper briefly summarized the role of ACE2 in SARS, and discussed the possible function of ACE2 in COVID-19 and potential risk of infection with other organs. At last, the function of ACE2 was explored for possible treatment strategies for SARS. It is hoped to provide ideas and theoretical support for clinical treatment of COVID-19.
Spike recorded by multi-channel microelectrode array is very weak and susceptible to interference, whose noisy characteristic affects the accuracy of spike detection. Aiming at the independent white noise, correlation noise and colored noise in the process of spike detection, combining principal component analysis (PCA), wavelet analysis and adaptive time-frequency analysis, a new denoising method (PCWE) that combines PCA-wavelet (PCAW) and ensemble empirical mode decomposition is proposed. Firstly, the principal component was extracted and removed as correlation noise using PCA. Then the wavelet-threshold method was used to remove the independent white noise. Finally, EEMD was used to decompose the noise into the intrinsic modal function of each layer and remove the colored noise. The simulation results showed that PCWE can increase the signal-to-noise ratio by about 2.67 dB and decrease the standard deviation by about 0.4 μV, which apparently improved the accuracy of spike detection. The results of measured data showed that PCWE can increase the signal-to-noise ratio by about 1.33 dB and reduce the standard deviation by about 18.33 μV, which showed its good denoising performance. The results of this study suggests that PCWE can improve the reliability of spike signal and provide an accurate and effective spike denoising new method for the encoding and decoding of neural signal.
ObjectiveTo investigate the efficacy and safety of Perampanel (PER) monotherapy in the treatment of self limited epilepsy with central temporal spikes (SeLECTS). Methods The clinical data of the first confirmed SelECTS in the outpatient and inpatient department of Xuzhou Children's Hospital affiliated to Xuzhou Medical University in December 2021 were collected, and the clinical data of PER monotherapy were retrospectively analyzed. The Seizure of 12 months old children were followed up to observe the efficacy and safety of PER monotherapy with spikes in the central temporal region, and the changes of Electroencephalography were observed. Result A total of 45 children with SeLECTS were included, of which 43 had complete medical records, including 13 males and 30 females, aged 4 ~ 14 years old, with a course of disease ranging from 1 month to 1.5 years. All 45 patients had focal seizures or focal secondary generalized tonic clonic seizures. Among them, 43 patients treated with PER alone for 12 months had epilepsy control efficacy rates of 74.41% (32/43) and no seizure rates of 60.46% (26/43), respectively. Seven children (15.56%, 7/45) experienced adverse reactions, characterized by dizziness, unstable gait, and irritability. Conclusion The third generation anti Seizure drug PER has a clear effect in the treatment of SelECTS, 2 ~ 4 mg PER can control Seizure well, and has no significant impact on cognitive development.
Both spike and local field potential (LFP) signals are two of the most important candidate signals for neural decoding. At present there are numerous studies on their decoding performance in mammals, but the decoding performance in birds is still not clear. We analyzed the decoding performance of both signals recorded from nidopallium caudolaterale area in six pigeons during the goal-directed decision-making task using the decoding algorithm combining leave-one-out and k-nearest neighbor (LOO-kNN). And the influence of the parameters, include the number of channels, the position and size of decoding window, and the nearest neighbor k value, on the decoding performance was also studied. The results in this study have shown that the two signals can effectively decode the movement intention of pigeons during the this task, but in contrast, the decoding performance of LFP signal is higher than that of spike signal and it is less affected by the number of channels. The best decoding window is in the second half of the goal-directed decision-making process, and the optimal decoding window size of LFP signal (0.3 s) is shorter than that of spike signal (1 s). For the LOO-kNN algorithm, the accuracy is inversely proportional to the k value. The smaller the k value is, the larger the accuracy of decoding is. The results in this study will help to parse the neural information processing mechanism of brain and also have reference value for brain-computer interface.
To explore the self-organization robustness of the biological neural network, and thus to provide new ideas and methods for the electromagnetic bionic protection, we studied both the information transmission mechanism of neural network and spike timing-dependent plasticity (STDP) mechanism, and then investigated the relationship between synaptic plastic and adaptive characteristic of biology. Then a feedforward neural network with the Izhikevich model and the STDP mechanism was constructed, and the adaptive robust capacity of the network was analyzed. Simulation results showed that the neural network based on STDP mechanism had good rubustness capacity, and this characteristics is closely related to the STDP mechanisms. Based on this simulation work, the cell circuit with neurons and synaptic circuit which can simulate the information processing mechanisms of biological nervous system will be further built, then the electronic circuits with adaptive robustness will be designed based on the cell circuit.