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Approximately 5% of advanced colorectal carcinomas (CRCs) and 12–15% of early CRCs are microsatellite instability-high (MSI-H) or mismatch repair-deficient (dMMR) tumors. Nowadays, PD-L1 inhibitors or combined CTLA4 inhibitors are the major strategies for advanced or metastatic MSI-H colorectal cancer, but some people still show drug resistance or progression. Combined immunotherapy has been shown to expand the benefit population in non-small-cell lung carcinoma (NSCLC), hepatocellular carcinoma (HCC), and other tumors while reducing the incidence of hyper-progression disease (HPD). Nevertheless, advanced CRC with MSI-H remains rare. In this article, we describe a case of an elder patient with MSI-H advanced CRC carrying MDM4 amplification and DNMT3A co-mutation who responded to sintilimab plus bevacizumab and chemotherapy as the first-line treatment without obvious immune-related toxicity. Our case provides a new treatment option for MSI-H CRC with multiple risk factors of HPD and highlights the importance of predictive biomarkers in personalized immunotherapy.

Microalgae has been regarded as a promising method for reducing CO2 emission. High CO2 concentration generally inhibits algal growth, and previous studies have mostly focused on breeding freshwater algae with high CO2 tolerance. In this study, one marine algal strain Dunaliella salina (D. salina) was grown under 0.03%-30 % CO2 and 3% NaCl conditions, and was evaluated to determine its potential for CO2 assimilation. The results showed that D. salina could tolerate 30% CO2, and its maximum biomass concentration could reach 1.13 g·L−1 after 8 days incubation, which was 1.85 times higher than that of incubation in air (0.03%). The phenomenon of high-CO2 tolerance in D. salina culture was discussed basing on transcriptome analysis. The results showed that D. salina was subjected to oxidative stress under 30% CO2 conditions, and the majority genes involving in antioxidant system, such as SOD, CAT, and APX genes were up-regulated to scavenge ROS. In addition, most of the key enzyme genes related to photosynthesis, carbon fixation and metabolism were up-regulated, which are consistent with the higher physiological and biochemical values for D. salina incubation under 30% CO2.

Supplemental Material for Dose-Response Association of Low and Normal Ankle Brachial Index With the Risk of Cardiovascular Disease Morbidity and Mortality by Jinli Zhang, Haohang Sun, Xingjin Yang, Yifei Feng, Yang Li, Minghui Han, Ranran Qie, Shengbing Huang, Lijun Yuan, Tianze Li, Huifang Hu, Xi Li, Dechen Liu, Xiaoyan Wu, Yanyan Zhang, Yuying Wu, Fulan Hu, Ming Zhang, Liang Sun, Dongsheng Hu, and Yang Zhao in Angiology

Infrared thermal image is an important medium for SF6 gas leakage detection. However, when the environment is complex or the temperature difference between the background and the measured gas is slight, a clear and obvious image can hardly be obtained. Moreover, the procedures for the leakage detection fully relies on human beings, which means lots of manpower are required and some subjective miss detection may occur. To solve this problem, aiming at the infrared thermal image and inspired by the breakthroughs in computer version (CV), this paper proposes a leakage detection method to realize automatic detection for the first time. Faster-RCNN, instead of human beings, is employed to handle SF6 infrared thermography image. Faster-RCNN is an advanced convolutional neural network, which has been widely used in numerous practical situations including image identification and face recognition. Under certain circumstances, our Faster-RCNN method can effectively improve the SF6 gas leakage detection. The method has great academic significance and can be promoted in practical engineering.

In recent years, abnormal behavior detection has become an active research field in computer vision and image processing. Several methods based on traditional two-stream CNN or 3D-CNN have been proposed and successfully applied in abnormal behavior detection. However, the abnormal behavior data is rarely less in the real scenario, in other words, the data is imbalanced, which may lead to overfitting problem and affect the final results. In this paper, an improved abnormal behavior detection method based on a two-stream CNN method was proposed to address the problem mentioned above. In the proposed method, DenseNet is adopted to extract both spatial and temporal features, and focal loss is employed to alleviate the influence of imbalanced data. The experiment results show that the proposed method provides a good performance in the real-world scenario.

A novel composite of LiFePO4 with phosphorus-doped carbon layers has been prepared via a simple hydrothermal method using glucose as the carbon source to generate a carbon coating and triphenylphosphine as the phosphorus source. The effects of phosphorus doping on the phase purity, morphology and electrochemical performance of the materials are studied by the characterizations using X-ray diffraction, Raman spectroscopy, scanning electron microscopy, high resolution transmission electron microscopy and electrochemical techniques. It is indicated that phosphorus doping into the carbon layers is beneficial for the graphitization of the carbon. Phosphorus in the carbon layers exists in the form of P–C bonds and its concentration depends on the second calcination temperature. Moreover, the phosphorus-doped carbon layers on the particle surface make the charge transfer resistance decrease remarkably from 156.5 Ω to 49.1 Ω, which can be ascribed to the free carriers donated by phosphorus. The as-prepared LiFePO4 with phosphorus-doped carbon layers calcined at 600 °C shows the best electrochemical performance with a discharge capacity of 124.0 mA h g−1 at a high rate of 20 C and an excellent retention rate of 91.4% after 50 cycles. The LiFePO4 with phosphorus-doped carbon layers exhibits excellent electrochemical performances, especially at high current rates; thus, it is a promising cathode material for high-performance lithium ion batteries.

The critical micelle concentration (CMC) of cetyl trimethylammonium bromide (CTAB) in both water and ethanol-water-mixed solvent was determined using steady-state fluorescence techniques in order to investigate the effect of the self-assembling properties of the surfactant on the template synthesis of porous inorganic materials. Results indicated that the CMC increased with the increase of ethanol concentration in the mixed solvent. The CMC of CTAB is 0.0009 mol/L in water, while it is 0.24 mol/L in ethanol. Furthermore, the dissipative particle dynamics (DPD) was adopted to simulate the aggregation of CTAB in water and ethanol/water mixtures, and the energy difference was calculated for the surfactant tail groups after mixing with the solvent. The simulation results reflected a regularity similar to the experimental data, i.e., tail groups of CTAB interacted more strongly with ethanol than with groups of CTAB interacted more strongly with ethanol than with water, which elucidates the reason that the micelle is difficult to form in ethanol.

The effects of debranning levels of 4 and 8% and ultra-fine grinding on physico-chemical, rheological, and pasting properties of wheat flour obtained from blue wheat, as well as cook quality, were investigated. The process of debranning decreased ash (from1.89 to 1.62%) and wet gluten content (from 44.68 to 38.81%), but increased the gluten index of wheat flours (from 12.95 to 17.82). Debranning had positive effects on color, rheological, pasting properties and quality of blue wheat cookies. The flours by kernel ultra-fine grinding had the highest wet gluten content (44.68%), L* value (87.14), water absorption (78.8 ml/100 mg), development time (4.7 min), cookie lightness (52.49) and the lowest particle diameter, b* value (2.92), and gluten index (12.95). Samples of bran ultra-fine grinding exhibited the maximum stability time (2.1min), resistance to extension (238 EU), paste viscosities, and the highest hardness, gumminess, and chewiness values of cookie dough. Debranning and ultra-fine grinding were useful in making the good properties of wheat flour and cookies. Key words: Blue wheat, debranning, ultra-fine grinding, cookies.

Wheat bran, shorts and feed flour are rich in dietary fiber and micronutrients. The effects of ultra-fine ground bran, shorts and feed flour on rheological characteristics of dough and bread qualities were investigated. Water absorption and dough development time gradually increased while mixing tolerance index and dough stability time decreased with the addition of bran, shorts and feed flour. The extension resistance and energy values for all blended flours were significantly higher than those of the control flour. The gluten index decreased while the gluten yield increased with the increase of bran, shorts and feed flour. Peak viscosity of the blended flour significantly decreased compared to the control flour. Pasting temperature rose from 67.05°C to 71.55, 72.6 and 69.25°C for bran, shorts and feed flour blends, respectively. The total scores of sensory evaluation and hardness of crumb texture significantly decreased with the increase of bran, shorts and feed flour.Key words: Ultra-fine grinding, bran, shorts, feed flour, rheological characteristic, bread quality

For small and medium manufacturing enterprise, in particular, multi-species, small and medium volume production enterprises, the management level of production logistics system is the key for the enterprise to utilize sufficiently all production capacity, to reduce the cost, to increase the effectiveness and improve the competitive capacity of product in the market. The problems of production logistics management system in small and medium manufacturing enterprise are analyzed, and based on the principles and procedures of improving the production logistics system performance, optimization design of production logistics management system is done, from factory layout, conveyance system, and balance of production and so on, to improve the management level of production logistics and the operation efficiency and profit. At the same time, according to the real demand of inventory management, the level of inventory management is improved on the basis of the quantitative indention model of the safe inventory and ABC method of inventory logistics. The mechanism of the automatic forecasting and alarming is realized and the upper limit and lower limit of inventory are set up to insure the continuity and stability of the product activity, the overstock and impropriation of the current capital is decreased.