Pattern formation of a pathway-based diffusion model: linear stability analysis and an asymptotic preserving method

We investigate the linear stability analysis of a pathway-based diffusion model (PBDM), which characterizes the dynamics of the engineered Escherichia coli populations [X. Xue and C. Xue and M. Tang, P LoS Computational Biology, 14 (2018), pp. e1006178]. This stability analysis considers small perturbations of the density and chemical concentration around two non-trivial steady states, and the linearized equations are transformed into a generalized eigenvalue problem. By formal analysis, when the internal variable responds to the outside signal fast enough, the PBDM converges to an anisotropic diffusion model, for which the probability density distribution in the internal variable becomes a delta function. We introduce an asymptotic preserving (AP) scheme for the PBDM that converges to a stable limit scheme consistent with the anisotropic diffusion model. Further numerical simulations demonstrate the theoretical results of linear stability analysis, i.e., the pattern formation, and the convergence of the AP scheme

Study on Parameter Optimization for Support Vector Regression in Solving the Inverse ECG Problem

The typical inverse ECG problem is to noninvasively reconstruct the transmembrane potentials (TMPs) from body surface potentials (BSPs). In the study, the inverse ECG problem can be treated as a regression problem with multi-inputs (body surface potentials) and multi-outputs (transmembrane potentials), which can be solved by the support vector regression (SVR) method. In order to obtain an effective SVR model with optimal regression accuracy and generalization performance, the hyperparameters of SVR must be set carefully. Three different optimization methods, that is, genetic algorithm (GA), differential evolution (DE) algorithm, and particle swarm optimization (PSO), are proposed to determine optimal hyperparameters of the SVR model. In this paper, we attempt to investigate which one is the most effective way in reconstructing the cardiac TMPs from BSPs, and a full comparison of their performances is also provided. The experimental results show that these three optimization methods are well performed in finding the proper parameters of SVR and can yield good generalization performance in solving the inverse ECG problem. Moreover, compared with DE and GA, PSO algorithm is more efficient in parameters optimization and performs better in solving the inverse ECG problem, leading to a more accurate reconstruction of the TMPs

Altered microglial response to Aβ plaques in APPPS1-21 mice heterozygous for TREM2

BACKGROUND: Recent genome-wide association studies linked variants in TREM2 to a strong increase in the odds of developing Alzheimer’s disease. The mechanism by which TREM2 influences the susceptibility to Alzheimer’s disease is currently unknown. TREM2 is expressed by microglia and is thought to regulate phagocytic and inflammatory microglial responses to brain pathology. Given that a single allele of variant TREM2, likely resulting in a loss of function, conferred an increased risk of developing Alzheimer’s disease, we tested whether loss of one functional trem2 allele would affect Aβ plaque deposition or the microglial response to Aβ pathology in APPPS1-21 mice. RESULTS: There was no significant difference in Aβ deposition in 3-month old or 7-month old APPPS1-21 mice expressing one or two copies of trem2. However, 3-month old mice with one copy of trem2 exhibited a marked decrease in the number and size of plaque-associated microglia. While there were no statistically significant differences in cytokine levels or markers of microglial activation in 3- or 7-month old animals, there were trends towards decreased expression of NOS2, C1qa, and IL1a in 3-month old TREM2(+/−) vs. TREM2(+/+) mice. CONCLUSIONS: Loss of a single copy of trem2 had no effect on Aβ pathology, but altered the morphological phenotype of plaque-associated microglia. These data suggest that TREM2 is important for the microglial response to Aβ deposition but that a 50% decrease inTREM2 expression does not affect Aβ plaque burden

An efficient ECG denoising method by fusing ECA-Net and CycleGAN

For wearable electrocardiogram (ECG) acquisition, it was easy to infer motion artifices and other noises. In this paper, a novel end-to-end ECG denoising method was proposed, which was implemented by fusing the Efficient Channel Attention (ECA-Net) and the cycle consistent generative adversarial network (CycleGAN) method. The proposed denoising model was optimized by using the ECA-Net method to highlight the key features and introducing a new loss function to further extract the global and local ECG features. The original ECG signal came from the MIT-BIH Arrhythmia Database. Additionally, the noise signals used in this method consist of a combination of Gaussian white noise and noises sourced from the MIT-BIH Noise Stress Test Database, including EM (Electrode Motion Artifact), BW (Baseline Wander) and MA (Muscle Artifact), as well as mixed noises composed of EM+BW, EM+MA, BW+MA and EM+BW+MA. Moreover, corrupted ECG signals were generated by adding different levels of single and mixed noises to clean ECG signals. The experimental results show that the proposed method has better denoising performance and generalization ability with higher signal-to-noise ratio improvement (SNRimp), as well as lower root-mean-square error (RMSE) and percentage-root-mean-square difference (PRD)

A guideline for economic evaluations of vaccines and immunization programs in China.

This study aimed to develop a consensus framework for economic evaluations of vaccines as a national guideline in China. Some unique and important aspects were particularly emphasized. Nineteen Chinese experts in the field of health economics and immunization decision-making were nominated to select and discuss relevant aspects of vaccine economic evaluations in China. A workshop attended by external experts was held to summarize unique and important aspects and formulate consensus recommendations. There were ten unique and/or important aspects identified for economic evaluations of vaccines in China, including study perspectives, comparator strategies, analysis types, model choices, costing approaches, utility measures, discounting, uncertainty, equity, and evaluation purposes. Background information and expert recommendations were provided for each aspect. Economic evaluations of vaccines should play an important role in China's immunization policy-making. This guideline can help improve the quality of economic evaluations as a good practice consensus

Two vacuolar invertase inhibitors PpINHa and PpINH3 display opposite effects on fruit sugar accumulation in peach

Soluble sugars are an important determinant of fruit taste, but their accumulation mechanisms remain elusive. In this study, we report two vacuolar invertase inhibitor genes involved in sugar accumulation in peach, PpINHa and PpINH3. Transient overexpression of PpINH3 in peach fruits resulted in an increase in sugar content, while the opposite trend was detected for PpINHa. Unexpectedly, PpINH3 and PpINHa both had no physical interaction with vacuolar invertase (VIN). Moreover, the PpVIN genes had no or extremely low expression in fruits at the ripening stage. These results suggested that the regulatory role of PpINHa and PpINH3 in sugar accumulation is unlikely due to their interaction with PpVINs. Additionally, overexpression of PpINHa and PpINH3 had an impact on transcription of genes related to fruit sugar metabolism and transport, which is likely responsible for their regulatory role in fruit sugar accumulation. Altogether, these results indicated an important role of PpINHs in fruit accumulation in peach. Our study provides new insights into molecular mechanisms underlying sugar accumulation, which could be useful for genetic improvement of fruit taste in breeding programs of peach and other fruit crops

Methane combustion in various regimes: first and second thermodynamic-law comparison between air-firing and oxyfuel condition

MILD oxyfuel combustion has been attracting increasing attention as a promising clean combustion technology. How to design a pathway to reach MILD oxyfuel combustion regime and what can provide a theoretical guide to design such a pathway are two critical questions that need to be answered. So far there has been no open literature on these issues. A type of combustion regime classification map proposed in our previous work, based on the so-called ”Hot Diluted Diffusion Ignition” (HDDI) configuration, is adopted here as a simple but useful tool to solve these problems. Firstly, we analyze comprehensively the influences of various dilution atmosphere and fuel type on combustion regimes. The combustion regime classification maps are made out according to the analyses. In succession, we conduct a comparison between the map in air-firing condition and its oxyfuel counterpart. With the aid of the second thermodynamic-law analysis on the maps, it is easy to identify the major contributors to entropy generation in various combustion regimes in advance, which is crucial for combustion system optimization. Moreover, we find that, for the first time, a combustion regime classification map also may be used as a safety indicator. With the aid of these maps, some conclusions in previous publications can be explained more straightforwardly