Two years ago, we described the first droplet digital PCR (ddPCR) system aimed at empowering all researchers with a tool that removes the substantial uncertainties associated with using the analogue ...standard, quantitative real-time PCR (qPCR). This system enabled TaqMan hydrolysis probe-based assays for the absolute quantification of nucleic acids. Due to significant advancements in droplet chemistry and buoyed by the multiple benefits associated with dye-based target detection, we have created a “second generation” ddPCR system compatible with both TaqMan-probe and DNA-binding dye detection chemistries. Herein, we describe the operating characteristics of DNA-binding dye based ddPCR and offer a side-by-side comparison to TaqMan probe detection. By partitioning each sample prior to thermal cycling, we demonstrate that it is now possible to use a DNA-binding dye for the quantification of multiple target species from a single reaction. The increased resolution associated with partitioning also made it possible to visualize and account for signals arising from nonspecific amplification products. We expect that the ability to combine the precision of ddPCR with both DNA-binding dye and TaqMan probe detection chemistries will further enable the research community to answer complex and diverse genetic questions.
Circular RNAs (circRNAs) and N
-methyladenosine (m
A) have been shown to play an increasingly critical role in the development of different cancers. However, there is limited evidence on how circRNAs ...and m
A interact to affect the radiosensitivity of cervical cancer (CC). This study provides a mechanistic understanding of the novel m
A-regulated circRNF13 in enhancing radioresistance in CC.
Differentially expressed circRNAs were identified from radiosensitive and radioresistant CC tissues. Meanwhile, these circRNAs were subjected to methylated RNA immunoprecipitation (Me-RIP). Finally, the effects of these circRNAs on radiosensitivity were characterized.
CircRNF13 was poorly expressed in CC patients that were sensitive to concurrent radiochemotherapy. Experiments conducted both in vitro and in vivo confirmed that the knockdown of circRNF13 potentiated the radiosensitivity of CC cells. Further mechanistic studies revealed that METTL3/YTHDF2 promoted the degradation of circRNF13 and subsequently affected the stability of CXC motif chemokine ligand 1 (CXCL1), ultimately enhancing the radiosensitivity of CC cells.
This study identified circRNF13 as a novel m
A-modified circRNA and validated the METTL3/YTHDF2/circRNF13/CXCL1 axis as a potential target for CC radiotherapy.
Acupuncturing the Zusanli (ST 36) point with different types of manual acupuncture manipulations (MAs) and different frequencies can evoke a lot of neural response activities in spinal dorsal root ...neurons. The action potential is the basic unit of communication in the neural response process. With the rapid development of the electrode acquisition technology, we can simultaneously obtain neural electrical signals of multiple neurons in the target area. So it is crucial to extract spike trains of each neuron from raw recorded data. To solve the problem of variability of the spike waveform, this paper adopts a optimization algorithm based on model to improve the wave-cluster algorithm, which can provide higher accuracy and reliability. Further, through this optimization algorithm, we make a statistical analysis on spike events evoked by different MAs. Results suggest that numbers of response spikes under reinforcing manipulations are far more than reducing manipulations, which mainly embody in synchronous spike activities.
Though Traditional Chinese Medicine (TCM) has long been playing a significant role in the maintenance of health for people in Asia as well as many other places, the mechanism of its action still ...remains ambiguous for most of the plants used in TCM, such as Eucommia ulmoides Oliv., a kind of herb that is widely used to help regulate hypertension and the immune system nowadays. However, its functioning mechanism is still unknown. Thus it is necessary to exploit the mechanism of Eucommia ulmoides Oliv.
A systems pharmacology approach combining drug-likeness evaluation, oral bioavailability prediction, multiple drug targets prediction as well as network pharmacology techniques has been used.
This comprehensive systematic approach helps successfully to identify 41 candidate compounds contained in Eucommia ulmoides Oliv. while 39 potential targets hit by these ingredients and helps to uncover the synergistic mechanism of action on a systematic level.
Our work successfully explains the mechanism of the efficiency of Eucommia ulmoides Oliv. for the treatment of hypertension and enhancing immune. These results not only provide a new insight for the understanding of the chemical and pharmacological basis of Eucommia ulmoides Oliv., but also provide an efficient way for drug discovery from herbal medicine.
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Diverse behaviors of the original Hodgkin–Huxley (HH) model, depending on the parameter values, have been studied extensively. This paper proposes modified HH equations exposed to externally applied ...extremely low frequency (ELF) electric fields. We investigate the effect of the DC electric fields on the dynamics of the modified HH model using bifurcation analysis. The obtained bifurcation sets partition the two dimensional parameter space, representing intensity of externally applied DC current and trans-membrane voltage induced by external DC electric fields, in terms of the qualitatively different behaviors of the HH model. Thus the neuronal information encodes the stimulus information, and vice versa. We also illustrate that the multi-stability phenomena in the HH model are associated with Hopf and double cycle bifurcations.
Seizure prediction can allow timely preventive measures for patients with epilepsy. In this study, we propose a hybrid model consisting of convolutional neural networks (CNNs) and an extreme learning ...machine (ELM) to predict seizures using scalp EEG. We first covert the EEG time series on 30-s windows into 2D spectrograms using the short-time Fourier transform. Then we apply CNNs to these images to extract features automatically. Finally, we use the ELM to classify preictal and interictal segments. The proposed method achieves sensitivity of 95.85% and a false prediction rate of 0.045/h on the Boston Children's Hospital-MIT scalp EEG dataset.
•A two-dimensional neuron model to extremely low frequency sinusoidal induced electric field (EF) is presented.•The dynamic behaviors of Hodgkin’s three classes of neuron are systematically ...analyzed.•Class 1 and 2 neurons exhibit similar spiking patterns by varying EF amplitude and frequency.•Class 3 neuron exhibits more complicated evolution procedures in the extremely low EF frequency area.•The induced EF parameters could determine and be quantified by neuronal spiking patterns.
To explore how extremely low frequency induced electric field (EF) interacts with neuronal activity, we introduce a sinusoidal induced EF into a two-dimensional neuron model and investigate the dynamic behaviors of Hodgkin’s three classes of neurons with different EF parameters, i.e., amplitude and frequency. It is observed that three classes of neurons can exhibit bursting, synchronous spiking and subthreshold oscillation when exposed to ELF induced EF. By analyzing neuronal spiking frequency and average firing rate, it is found that class 1 and 2 neurons could generate bursting with p:1 (p>1) phase-locking in the low EF frequency area when EF amplitude is above the stimulus spiking threshold, whereas class 3 neuron is not so sensitive to induced EF stimulus in this area unless the EF amplitude is much higher. With the increase of EF frequency, three classes of neurons all exhibit synchronous spiking with 1:1 phase-locking. When EF frequency further increases, the spiking frequency for three classes will drop to zero and neurons cease spiking. Our study suggests that the induced EF parameters can determine and be quantified by neuronal spiking patterns. It can contribute to reveal how EF stimulus is encoded by different neurons, which may aid the interpretation of the effects of electromagnetic fields on brain neurons.
In this paper, a high speed visible light communication transceiver module is designed, and a 100Mbps white light LED based visible light communication system is constructed based on this module. ...Without using a blue filter, we combined the pre-emphasis technology, modulation technology and the back-end equalization technology to improve the bandwidth and data transmission rate of the visible light communication system effectively. The system has advantages of low cost, low complexity, low power consumption and small transceiver module, which can be practical and industrialized.
This paper presents an adaptive anticipatory synchronization based method for simultaneous identification of topology and parameters of uncertain nonlinearly coupled complex dynamical networks with ...time delays. An adaptive controller is proposed, based on Lyapunov stability theorem and Barbǎlat's Lemma, to guarantee the stability of the anticipatory synchronization manifold between drive and response networks. Meanwhile, not only the identification criteria of network topology and system parameters are obtained but also the anticipatory time is identified. Numerical simulation results illustrate the effectiveness of the proposed method.
Neuron as the main information carrier in neural systems is able to generate diverse fire trains in response to different stimuli. In this paper, the stimulus frequency is taken as the bifurcation ...parameter, and ISI is considered to be one of the state variables. Via numerical simulation, we mainly concentrate on the kinds of fire patterns that the modified HH neuron model displays such as period-
n, bursting, and modulation fire patterns, etc. under the effect of external sinusoidal ELF electric field, and the relation between the ISI sequences and the external stimulus just like synchronization and transition in the manner of pitchfork bifurcation. In addition, an explanation is put forwards from the electrophysiology point of view to try to interpret why neurons generate so many different kinds of ISI sequences.
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