Search

Abstract Background The molecular and immunological characteristics of primary tumors and positive lymph nodes in esophageal squamous cell carcinoma (ESCC) are unknown and the relationship with recurrence is unclear, which this study attempted to explore. Methods A total of 30 ESCC patients with lymph node positive (IIB‐IVA) were enrolled. Among them, primary tumor and lymph node specimens were collected from each patient, and subjected to 551‐tumor‐targeted DNA sequencing and 289‐immuno‐oncology RNA panel sequencing to identify the different molecular basis and immunological features, respectively. Results The primary tumors exhibited a higher mutation burden than lymph nodes (p

Abstract Background It is yet unknown if the whole-brain resting-state network is altered in multiple system atrophy with symptoms of depression. This study aimed to investigate if and how depression symptoms in multiple system atrophy are associated with resting-state network dysfunction. Methods We assessed the resting-state functional network matric using Degree centrality (DC) coupling with a second ROI-wise functional connectivity (FC) algorithm in a multimodal imaging case-control study that enrolled 32 multiple system atrophy patients with depression symptoms (MSA-D), 30 multiple system atrophy patients without depression symptoms (MSA-ND), and 34 healthy controls (HC). Results Compared to HC, MSA-D showed more extensive DC hub dysfunction in the left precentral and right middle frontal cortex than MSA-ND. A direct comparison between MSA-D and MSA-ND detected increased DC in the right anterior cingulum cortex, but decreased DC in the left cerebellum lobule IV and lobule V, left middle pole temporal cortex, and right superior frontal cortex. Only right anterior cingulum cortex mean DC values showed a positive correlation with depression severity, and used ACC as seed, a second ROI-wise functional connectivity further revealed MSA-D patients showed decreased connectivity between the ACC and right thalamus and right middle temporal gyrus (MTG). Conclusions These findings revealed that dysfunction of rACC, right middle temporal lobe and right thalamus involved in depressed MSA. Our study might help to the understanding of the neuropathological mechanism of depression in MSA.

Information exchange between brain regions is key to understanding information processing for social decision-making, but most analyses ignore its dynamic nature. New insights on this dynamic might help us to uncover the neural correlates of social cognition in the healthy population and also to understand the malfunctioning neural computations underlying dysfunctional social behavior in patients with mental disorders. In this work, we used a multi-round bargaining game to detect switches between distinct bargaining strategies in a cohort of 76 healthy participants. These switches were uncovered by dynamic behavioral modeling using the hidden Markov model. Proposing a novel model of dynamic effective connectivity to estimate the information flow between key brain regions, we found a stronger interaction between the right temporoparietal junction (rTPJ) and the right dorsolateral prefrontal cortex (rDLPFC) for the strategic deception compared with the social heuristic strategies. The level of deception was associated with the information flow from the Brodmann area 10 to the rTPJ, and this association was modulated by the rTPJ-to-rDLPFC information flow. These findings suggest that dynamic bargaining strategy is supported by dynamic reconfiguration of the rDLPFC-and-rTPJ interaction during competitive social interactions.

Background: The molecular and immunological characteristics of primary tumors and positive lymph nodes in esophageal squamous cell carcinoma (ESCC) are unknown and the relationship with recurrence is unclear, which this study attempted to explore. Methods: A total of 30 ESCC patients with lymph node positive (IIB‐IVA) were enrolled. Among them, primary tumor and lymph node specimens were collected from each patient, and subjected to 551‐tumor‐targeted DNA sequencing and 289‐immuno‐oncology RNA panel sequencing to identify the different molecular basis and immunological features, respectively. Results: The primary tumors exhibited a higher mutation burden than lymph nodes (p < 0.001). One‐year recurrent ESCC exhibited a higher Mucin16 (MUC16) mutation rate (p = 0.038), as well as univariate and multivariate analysis revealed that MUC16 mutation is independent genetic factor associated with reduced relapse‐free survival (univariate, HR: 5.39, 95% CI: 1.67–17.4, p = 0.005; multivariate, HR: 7.36, 95% CI: 1.79–30.23, p = 0.006). Transcriptomic results showed non‐relapse group had higher cytolytic activity (CYT) score (p = 0.025), and was enriched in the IFN‐α pathway (p = 0.036), while those in the relapsed group were enriched in the TNF‐α/NF‐κB (p = 0.001) and PI3K/Akt pathway (p = 0.014). Conclusion: The difference in molecular characteristics between primary lesions and lymph nodes may be the cause of the inconsistent clinical outcomes. Mutations of MUC16 and poor immune infiltration are associated with rapid relapse of nodes‐positive ESCC. [ABSTRACT FROM AUTHOR]

This paper reveals novel properties of spectrum of linear delay differential systems, and concerns the stability of a general class of time delay systems. The stability issue can be well characterized by the distribution of spectrum of the associated characteristic equation. Benefit properties on finite and bounded are formulated. And the finiteness condition and distribution boundary are obtained in a practical way. Based on the argument principle, an analytical formula for computing the number of unstable zeros (with positive real part) is deduced, which is determined by definite integral. Moreover, a procedure put no restriction on system except for the delay engendering purely imaginary roots is proposed to investigate the stability of linear time delay systems. At last, typical examples are given to illustrate that the method carried out is reliable and efficient.

High-performance gas sensors have been developed to meet the demand for trace detection of NO2, given the adverse effects of NO2 on the environment and human health. Two-dimensional (2D) metal oxides are considered an emerging class of NO2-sensitive materials. However, their controllable synthesis and poor recovery are two major obstacles to practical NO2 sensing applications. In this study, we prepare tailorable 2D p-type SnO nanosheets with thicknesses between 1.5 and 3 nm by precisely controlling self-limiting oxidation over the liquid Sn surface. At an oxygen concentration of 0.05%, 2D SnO nanosheets exhibit a lateral dimension as large as 100 μm with a thickness of 1.5 nm, which can be facilely integrated into a field-effect transistor (FET) platform to form 2D devices. The NO2 sensing performance of 2D SnO at room temperature is investigated under excitation of a broad range of UV-Visible light. The optimum response magnitude to 10 ppm NO2 is achieved at ∼205% at 450 nm excitation with excellent reversibility. In addition, the selectivity for NO2 is also explored, indicating an up to one order enhancement over those of CO2, NH3, H2, H2S, CO, and CH4. We ascribe this improved performance to the optimum band alignment between 1.5 nm-thick SnO and NO2 gas molecules. This work provides a feasible approach to prepare 2D metal oxide nanosheets and demonstrates that they have great potential for fully reversible gas sensing at room temperature. [ABSTRACT FROM AUTHOR]

Seizures are caused by increased neuronal firing activity resulting from reduced inhibitory effect and enhancement of inhibitory modulation to suppress this activity is used as a therapeutic tool. However, recent experiments have shown a counterintuitive phenomenon that inhibitory modulation does not suppress but elicit post-inhibitory rebound (PIR) spike along with seizure to challenge the therapeutic tool. The nonlinear mechanism to avoid the PIR spike can present theoretical guidance to seizure treatment. This paper focuses on identifying credible bifurcations that underlie PIR spike by modulating multiple parameters in multiple theoretical models. The study identifies a codimension-2 bifurcation called saddle--node homoclinic orbit (SNHOB), which is an intersection between saddle node bifurcation on invariant cycle (SNIC) and other two bifurcations. PIR spike cannot be evoked for the SNIC far from the SNHOB but induced for the SNIC close to the SNHOB, which extends the bifurcation condition for PIR spike from the well-known Hopf to SNIC. Especially, in a thalamic neuron model, increases of conductance of T-type Ca2+ (T Ca) channel induce SNIC bifurcation approaching to the SNHOB to elicit PIR spikes, closely matching experimental results of the absence seizure or Parkinson diseases. Such results imply that, when inhibition is employed to relieve absence seizure and Parkinson diseases related to PIR spike, modulating SNIC to get far from the SNHOB to avoid PIR spike is the principle. The study also addresses the complex roles of T Ca current and comprehensive relationships between PIR spike and nonlinear conceptions such as bifurcation types and shapes of threshold curve. [ABSTRACT FROM AUTHOR]

This paper proposes a new method for assessing the vulnerability of power systems based on the controllability theories of complex networks. A novel controllability index is established, taking into consideration the full controllability of the power systems, for identifying critical nodes. The network controllability model is used to calculate the minimum number of driver nodes (ND), which can solve the computable problems of the controllability of power systems. The proposed approach firstly applies the network controllability theories to research the power systems' vulnerability, which can not only effectively reveal the important nodes but also maintain full control of the power systems. Meanwhile, the method can also overcome the limitation of the hypothesis that the weight of each link or transmission line must be known compared with the existing literature. In addition, the power system is considered as a directed network and the power system model is also redefined. The proposed methodology is then used to identify critical nodes of the IEEE 118 and 300 bus system. The results show that the failure of the critical nodes can clearly increase ND and lead a significant driver node shift. Thus, the rationality and validity are verified.

Background: Recurrent stroke is often devastating, and can cause severe disability or death. Risk factors associated with recurrent strokes unrelated to atrial fibrillation have been well identified; however, it remains to be further elucidated whether the risk factors for recurrent stroke are the same in young as in older patients. Methods: Data from 1017 stroke patients unrelated to atrial fibrillation were retrospectively reviewed. Risk factors analyzed included sex, smoking history, previous history of ischemic stroke or transient ischemic attack, hypertension, diabetes mellitus, coronary atherosclerotic heart disease, and previous myocardial infarction. All patients were followed up via telephone 1 year after their initial strokes. Logistic regression was used to assess the associations between the various factors and risk of recurrent stroke events. Results: Predictive independent risk factors of recurrent stroke in older men included previous history of myocardial infarction [odds ratio (OR), 6.761; 95% confidence interval (CI), 1.030–44.371], ischemic stroke or transient ischemic attack (OR, 2.496; 95% CI, 1.567–3.976), diabetes mellitus (OR, 1.986; 95% CI, 1.223–3.227), and coronary atherosclerotic disease (OR, 1.733; 95% CI, 1.010–2.974). In young men, hypertension (OR, 1.709; 95% CI, 1.104–2.645), coronary atherosclerotic heart disease (OR, 1.812; 95% CI, 1.129–2.911), and previous history of ischemic stroke or transient ischemic attack (OR, 2.317; 95% CI, 1.580–3.397) were independent risk factors of recurrent strokes. Conclusion: The predictive independent risk factors of recurrent stroke differ between young and older stroke patients. Our findings may help guide the prevention of recurrent strokes.

Background: The relationship between monosymptomatic resting tremor (mRT) and Parkinson′s disease (PD) remains controversial. In this study, we aimed to assess the function of presynaptic dopaminergic neurons in patients with mRT by dopamine transporter positron emission tomography (DAT-PET) and to evaluate the utility of clinical features or electrophysiological studies in differential diagnosis. Methods: Thirty-three consecutive patients with mRT were enrolled prospectively. The Unified Parkinson′s Disease Rating Scale and electromyography were tested before DAT-PET. Striatal asymmetry index (SAI) was calculated, and a normal DAT-PET was defined as a SAI of

One-dimensional (1D)/two-dimensional (2D) heterostructures offer attractive opportunities for developing high-performance gas sensors because of the unique built-in electric field at the hetero-interface, efficient charge separation and transportation, and synergetic properties of the 1D and 2D components. However, a relatively high operating temperature, insufficient gas sensitivity, and complex fabrication process present the key challenges for practical implementation. Here, we realize a p-type 1D/2D heterostructure consisting of Se belts and GeSexOy nanosheets through a single-step synthesis governed by the exfoliation–nucleation process. A type II band alignment configuration is found in the heterostructure with an effective bandgap energy of ∼1.32 eV, which covers the complete visible light spectrum. The visible-light-driven optoelectronic NO2 gas sensing performances are then investigated at room temperature. A ∼27.3% response magnitude towards 10 ppm NO2 is achieved upon irradiation with red light, with a sub-ppb limit of detection, full reversibility, excellent selectivity, and >3 months long-term stability, which is a significant improvement as a whole over those of reported 1D/2D heterostructure-based room temperature NO2 sensors. This work paves the way for realizing mixed-dimensional heterojunction-based next-generation gas sensors in a facile and effective manner. [ABSTRACT FROM AUTHOR]

Nowadays, artificial intelligence and computer vision have been applied in various domains in the real world, such as Autonomous vehicles, video surveillance, human activity recognition, face recognition, smart home, and automated industry. Video-based human activity recognition is a big challenge yet. This paper proposes the Gaussian Mixture Model and Optical Flow approach to detect foreground and feature extraction for human activity recognition. The speed with a range of frames and radial distance from the Centroid to edge points of the human silhouette describe the feature vector of human activities. And then, the features are classified by multi-class SVM. The proposed system has been tested in the Weizmann datasets and KTH datasets. The experiment shows that our methods distinguish walking, bending, running, and wave-hand efficiently and accurately. [ABSTRACT FROM AUTHOR]

Poly(ethylene terephthalate) (PET) waste from local market was depolymerized by ethylene glycol (EG) in the presence of metal-containing ionic liquids, and the qualitative analysis showed that the bis(hydroxyethyl) terephthalate (BHET) was the main product in this process. Compared with other metal-containing ionic liquids, [Bmim]ZnCl3 was considered the best catalyst in the glycolysis of PET. When the reaction temperature was 180°C, the conversion of PET reached 97.9% and the BHET was yielded to 83.3% within 5 h. At the same time, [Bmim]ZnCl3 could be reused for six times without obvious decrease in the yield of BHET. Additional, the effects of waste PET’s source and size were investigated.

To analyze the electromagnetic scattering characteristics of stealth targets, radar cross section (RCS) values of the typical stealth aircraft model are evaluated by electromagnetic simulation. Based on the RCS electromagnetic simulation results, RCS statistical histograms of the stealth aircraft model are created. For describing the RCS statistical characteristics of stealth aircrafts, a Weibull‐generalized gamma mixture distribution model is proposed in this study. Some special cases of the Weibull‐generalized gamma mixture distribution model are summarized. Utilizing the nonlinear least squares technique, fitting results of the proposed and conventional RCS distribution models for the RCS statistical characteristics of typical stealth aircarfts are compared. Mean square error test and R‐square (R2 ${R}^{2}$) test results show that the proposed distribution model obtains better fitting results than the conventional RCS distribution models, which indicates that the proposed distribution model is a more efficient RCS statistical model. [ABSTRACT FROM AUTHOR]

The design of high-resolution and cross-term (CT) free time-frequency distributions (TFDs) has been an open problem. Classical kernel based methods are limited by the trade-off between resolution and CT suppression, even under optimally derived parameters. To break the current limitation, we propose a data-driven model directly based on Wigner-Ville distribution (WVD). The proposed data-driven high-resolution TFD (DH-TFD) includes several stacked multi-channel convolutional kernels. Specifically, convolutional layers with skipping operators are utilized to learn coarse features, while a weighted block is employed to refine these features independently in both channel and spatial dimensions. By doing so, CTs can be effectively eliminated while maintaining a high resolution. Numerical experiments on both synthetic and real-world data confirm the superiority of the proposed DH-TFD in simultaneously extracting and representing a target signal over state-of-the-art methods. [ABSTRACT FROM AUTHOR]

In this paper, a novel distributed method is presented to solve combined heat and power economic dispatch problem, which is formulated as a distributed coupled optimization problem. The optimization goal is achieved by establishing two modified consensus protocols with two corresponding feedback parts while satisfying the electrical and heat supply–demand balance. Moreover, an alternating iterative method is proposed to handle the heat-electrical coupling problem existed in the objective function and the feasible operating regions. In addition, the proposed distributed method is implemented by a multi-agent system framework, which only requires local information exchange among neighboring agents. Simulation results obtained on a 16-bus test system are provided to illustrate the effectiveness of the proposed distributed method.

The method of moments solution on integral equations for electromagnetic scattering and radiation problems with Rao--Wilton--Glisson (RWG) and n x RWG basis functions requires the calculation of singular double surface integrals over triangular subdomains. In this paper, an approach is presented to deal with the singularity and almost singularity in which the triangle subdomain is divided into several subtriangles and then the singular or almost singular integral is calculated over each of the subtriangles. This approach is mainly based on the projection process and the local polar frame. It can be used to deal with the singular double surface integrals of order 1/R and 1/[R.sup.2], in which vector functions may be of zeroth-order and higher order. Numerical examples are provided to verify the validity of the method presented in this paper for dealing with the singularity and almost singularity. Index Terms--Curl-conforming vector function, divergence-conforming vector function, method of moments (MoM), Rao-Wilton--Glisson (RWG) function.