Inkjet printing technology is expected to enhance printed display mass production technology in the future. Nozzle-array printheads form the basis for printed display mass production applications. ...However, jet instability caused by air bubble entrapment and nozzle wettability changes during the printing process is a major challenge in the application of this technology. To adapt to possible nozzle abnormalities, a high-adaptability nozzle-array printing system based on a set covering printing planning (SCPP) model for printed display manufacturing is designed in this study. The study consists of two parts. First, a printing system based on multistep visual inspection and closed-loop feedback is proposed to accurately detect and screen abnormal nozzle positions. Notably, the inkjet printing system can identify nozzles with abnormal ejection characteristics and ensure that the remaining nozzles work accurately and stably. Then, an SCPP model is established for display pixel printing planning by using the remaining normal nozzles on the nozzle-array printhead. This model can output the most efficient printing path and nozzle printing action and can adapt to any pixel pattern, nozzle type, and abnormal nozzle distribution. The system and technology are highly adaptable and scalable for fabricating large-area printed display devices.
An accurate and reliable traffic flow prediction is of great significance, especially the long-term traffic flow prediction e.g., 24 hours, which can help the traffic decision-makers formulate the ...future traffic management strategy. However, the long-term traffic flow prediction imposes great challenges for decision-makers due to the nonlinear and chaotic feature of traffic flow. Therefore, in this paper, we proposed a hybrid deep learning model based on wavelet decomposition, convolutional neural network-long and short-term memory neural network (CNN-LSTM), called W-CNN-LSTM, to prediction next-day traffic flow. The wavelet decomposition technology is used to decompose the original traffic flow data into high-frequency data and low-frequency data for the improvement of predictive accuracy. The decomposed sequences are fed into a CNN-LSTM deep learning model, where the long-term temporal features of traffic flow can be well captured and learned. The numerical experiment is carried out against five benchmarks based on England traffic flow dataset; the results show that the proposed hybrid approach can achieve superior forecasting skill over the benchmarks.
Lung cancer has higher morbidity and mortality than most cancers. It is common that there are some phenomenons of secondary drug resistance, radiotherapy resistance and poor prognosis during the ...treatment of small cell lung cancer (SCLC). Recent studies revealed that the single-nucleotide polymorphisms (SNPs) are associated with the curative effect among patients with the same pathological type and stage. Our study analyzed the start time of radiotherapy and the relationship between PTEN gene rs2299939 polymorphisms and survival time among 116 SCLC patients. The results showed that early radiotherapy significantly improved the time of survival in patients compared with late radiotherapy (
= 0.029). Simultaneously, the study found that patients with the rs2299939 AA genotype showed significant sensitivity to both early and late radiotherapy, but early radiotherapy is better. The median survival time of CC genotype patients was 12 months in the early radiotherapy group while it was 9 months in the late radiotherapy group, thus recommending early radiotherapy among these patients. In addition, it was found that rs2299939 could regulate the expression of related genes in peripheral blood and lung tissues by eQTL analysis. This study revealed that the early radiotherapy could prolong the PFS of SCLC and shall be performed in SCLC treatment.
Glabridin (Glab) is a bioactive component of licorice that can ameliorate diabetes, but its role in diabetic nephropathy (DN) has seldom been reported. Herein, we explored the effect and underlying ...mechanism of Glab on DN.
The bioactive component-target network of licorice against DN was by a network pharmacology approach. The protective effect of Glab on the kidney was investigated by a high-fat diet with streptozotocin induced-diabetic rat model. High glucose-induced NRK-52E cells were used for in vitro studies. The effects of Glab on ferroptosis and VEGF/Akt/ERK pathways in DN were investigated in vivo and in vitro using qRT-PCR, WB, and IHC experiments.
Bioinformatics analysis constructed a network comprising of 10 bioactive components of licorice and 40 targets for DN. 13 matching targets of Glab were mainly involved in the VEGF signaling pathway. Glab treatment ameliorated general states and reduced FBG, HOMA-β, and HOMA-insulin index of diabetic rats. The renal pathological changes and the impaired renal function (the increased levels of Scr, BUN, UREA, KIM-1, NGAL, and TIMP-1) were also improved by Glab. Moreover, Glab repressed ferroptosis by increasing SOD and GSH activity, and GPX4, SLC7A11, and SLC3A2 expression, and decreasing MDA and iron concentrations, and TFR1 expression, in vivo and in vitro. Mechanically, Glab significantly suppressed VEGF, p-AKT, p-ERK1/2 expression in both diabetic rats and HG-induced NRK-52E cells.
This study revealed protective effects of Glab on the kidney of diabetic rats, which might exert by suppressing ferroptosis and the VEGF/Akt/ERK pathway.
A palladium-based catalyst (Fe3O4/SiO2/HPG–OPPh2–PNP) supported on chlorodiphenylphosphine-functionalized magnetic nanoparticles was successfully prepared from Fe3O4/SiO2 with sequential attachment ...of glycerol and chlorodiphenylphosphine, followed by treatment of an ethanolic solution of palladium chloride with hydrazine. The as-prepared catalyst was characterized by ICP-AES, FTIR, XRD, SEM, and TEM. The Fe3O4/SiO2/HPG–OPPh2–PNP was found as a magnetically separable and highly active catalyst for Suzuki coupling reactions of aryl iodides, bromides, and chlorides as well as Heck reactions of aryl iodides and bromides. Under appropriate conditions, all reactions afforded the desired products in moderate to excellent yields. Moreover, this catalyst can be easily recovered by using a magnetic field and directly reused for at least six cycles without significant loss of its activity.
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The motion planning module is the core module of the automated vehicle software system, which plays a key role in connecting its preceding element, i.e., the sensing module, and its following ...element, i.e., the control module. The design of an adaptive polar lattice-based local obstacle avoidance (APOLLO) algorithm proposed in this paper takes full account of the characteristics of the vehicle's sensing and control systems. The core of our approach mainly consists of three phases, i.e., the adaptive polar lattice-based local search space design, the collision-free path generation and the path smoothing. By adjusting a few parameters, the algorithm can be adapted to different driving environments and different kinds of vehicle chassis. Simulations show that the proposed method owns strong environmental adaptability and low computation complexity.
T-cell receptor (TCR) is crucial in T cell-mediated virus clearance. To date, TCR bias has been observed in various diseases. However, studies on the TCR repertoire of COVID-19 patients are lacking. ...Here, we used single-cell V(D)J sequencing to conduct comparative analyses of TCR repertoire between 12 COVID-19 patients and 6 healthy controls, as well as other virus-infected samples. We observed distinct T cell clonal expansion in COVID-19. Further analysis of VJ gene combination revealed 6 VJ pairs significantly increased, while 139 pairs significantly decreased in COVID-19 patients. When considering the VJ combination of α and β chains at the same time, the combination with the highest frequency on COVID-19 was TRAV12-2-J27-TRBV7-9-J2-3. Besides, preferential usage of V and J gene segments was also observed in samples infected by different viruses. Our study provides novel insights on TCR in COVID-19, which contribute to our understanding of the immune response induced by SARS-CoV-2.
•We performed single-cell V(D) J sequencing for 12 COVID-19 patients.•Comparative analyses of TCR repertoire between COVID-19 patients and controls, as well as other virus-infected samples.•TCR clonal diversity is significantly reduced in COVID-19 patients.•Preferential usage of T cell receptor is significantly different in several viral infections.
The digital economy is promoting rural development and rural residents’ income growth and realizing the improvement of supply efficiency and the change of factor power. In this paper, we first ...construct the measurement system of rural residents’ income level and digital economy development level, respectively, and then use big data technology to collect relevant data from 2013 to 2020 and calculate the development level of the two by using principal component analysis and entropy weight method respectively. Then, the level of digital economy development was taken as an explanatory variable. Rural residents’ income was taken as an explanatory variable. Empirical regression analysis was carried out to explore the impact of digital economy on the improvement of rural residents’ income. The mediation effect and regional heterogeneity test were carried out. The results show that the coefficients of the digital economy are always significant and all positive at a 1% level when control variables are added gradually, and the Sobel statistic of entrepreneurial activity is 0.061 and 0.045. This study provides theoretical support for the analysis of how the rural digital economy can promote the revitalization of rural industries and promote the commonwealth of farmers and rural areas.
To characterize the clinical and pathological features and survival of patients with human epidermal growth factor receptor 2 (HER2)-low breast cancer in China.
The China National Cancer Center ...database was used to identify 1,433 metastatic breast cancer patients with HER2-negative disease diagnosed between 2005 and 2015. Clinicopathological features, survival, and prognosis information were extracted. Overall survival (OS) was estimated using the Kaplan-Meier method and compared using the log-rank test. Prognostic factors associated with OS were analyzed using Cox regression model with 95% confidence interval (95% CI).
There were 618 (43.1%) and 815 (56.9%) HER2-low and HER2-zero tumors out of 1,433 tumors, respectively. The proportion of hormone receptor (HR)-positive tumors was significantly higher in HER2-low tumors than in those with HER2-zero tumors (77.8% vs. 69.2%,
< 0.001). Patients with HER2-low tumors survived significantly longer than those with HER2-zero tumors in the overall population (48.5 months vs. 43.0 months,
= 0.004) and HR-positive subgroup (54.9 months vs. 48.1 months,
= 0.011), but not in the HR-negative subgroup (29.5 months vs. 29.9 months,
= 0.718). Multivariate regression analysis revealed that HER2-low tumors were independently associated with increased OS in HER2-negative population (HR: 0.85, 95% CI: 0.73-0.98,
= 0.026).
Our findings demonstrate that HER2-low tumors could be identified as a more distinct clinical entity from HER2-zero tumors, especially for the HR-positive subgroup. A more complex molecular landscape of HER2-low breast cancer might exist, and more precise diagnostic algorithms for HER2 testing could be investigated, thus offering new therapeutic targets for breast cancer treatment.
Abstract Objectives This study examined the relationship of social isolation and loneliness on sarcopenia among Chinese middle-aged and elderly people. Methods Social isolation, loneliness, and ...sarcopenia were measured at baseline. Follow-up measures of new-onset sarcopenia were obtained 4 years later. Then used logistic regression to evaluate the association between social isolation, loneliness and sarcopenia. Results In cross-sectional analysis, social isolation and loneliness are significantly associated with sarcopenia OR = 1.88 (95% CI = 1.54–2.28). In longitudinal analysis, social isolation and loneliness are significantly associated with sarcopenia OR = 1.09 (95% CI = 0.71–1.69). Social isolation and loneliness have a synergistic effect. Among them, individuals over 60 years old OR = 2.01 (95% CI = 1.37–2.96) and those without social support OR = 2.64 (1.61–4.32), P -for interaction < 0.001 are at higher risk. Conclusion Social isolation and loneliness were significantly associated with sarcopenia, and there was a synergistic effect between social isolation and loneliness.
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