Evaluation of Anti-tumor and Chemoresistance-lowering Effects of Pectolinarigenin from Cirsium japonicum Fisch ex DC in Breast Cancer

Purpose: To investigate the antitumor and chemoresistance-lowering effects of pectolinarigenin on breast cancer cells.Methods: Pectolinarigenin was purified by a combination of silica gel and Sephadex LH-20 column chromatography from ethanol extracts of the aerial parts of C. japonicum DC. Breast cancer selfrenewal properties were tested by colony formation and tumor sphere formation assays. Thereafter, real-time polymerase chain reaction (PCR) was used to detect breast cancer stem cell markers. Furthermore, the effect of pectolinarigenin on breast cancer cell was evaluated by chemoresistance using 3-(4,5-dimethyl-2 thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) assay. Finally, tumor formation in nude mice was used to test the effect of pectolinarigenin on tumorigenicity of breast cancer cells in vivo.Results: The results showed that pectolinarigenin, extracted from Cirsium japonicum Fisch. ex DC., inhibited tumor cell self-renewal in MCF-7 breast cancer cells. Pectolinarigenin (25 μM) caused significant inhibition of colony formation (61.23 %, p < 0.001) and tumor sphere formation (59.49 %, p < 0.01) in MCF-7. The inhibitory effects were associated with changes in breast cancer stem cell markers. Treatment of breast cancer cells with pectolinarigenin reduced the chemoresistance of the cells to doxorubicin. At the same time, mRNA expression of chemoresistance genes (ATP binding cassette subfamily G member 2, ABCG2 and ATP binding cassette subfamily B member 1, MDR1) was repressed by pectolinarigenin. The inhibition efficiency of MDR1 and ABCG2 by 10 μM pectolinarigenin treatment was about 59.29 (p < 0.01) and 46.48 % (p < 0.01), respectively. Furthermore, pectolinarigenin reduced tumor mass in nude mice xenograft model.Conclusion: Pectolinarigenin inhibits breast cancer stem cell-like properties and lowers the chemoresistance of the cancer cells to chemotherapy. The results provide an insight into the mechanism of the anti-breast tumor effects and an experimental basis for the use of pectolinarigenin to enhance treatment of patients with breast cancer.Keywords: Pectolinarigenin, Cancer stem cells, Breast cancer, Chemoresistance, Cirsium japonicum Fisch. ex D

Polymeric pH nanosensor with extended measurement range bearing octaarginine as cell penetrating peptide

A synthetic peptide octaarginine which mimics human immunodeficiency virus‐1, Tat protein is used as cell penetrating moiety for new pH nanosensors which demonstrate enhanced cellular uptake and expanded measurement range from pH 3.9 to pH 7.3 by simultaneously incorporating two complemental pH‐sensitive fluorophores in a same nanoparticle. The authors believe that this triple fluorescent pH sensor provides a new tool to pH measurements that can have application in cellular uptake mechanism study and new nanomedicine design

Baichuan 2: Open Large-scale Language Models

Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering. However, most powerful LLMs are closed-source or limited in their capability for languages other than English. In this technical report, we present Baichuan 2, a series of large-scale multilingual language models containing 7 billion and 13 billion parameters, trained from scratch, on 2.6 trillion tokens. Baichuan 2 matches or outperforms other open-source models of similar size on public benchmarks like MMLU, CMMLU, GSM8K, and HumanEval. Furthermore, Baichuan 2 excels in vertical domains such as medicine and law. We will release all pre-training model checkpoints to benefit the research community in better understanding the training dynamics of Baichuan 2.Comment: Baichuan 2 technical report. Github: https://github.com/baichuan-inc/Baichuan

Does Regional Innovation Environment Have an Impact on the Gathering of Technological Talent? An Empirical Study Based on 31 Provinces in China

Driven by innovation, the implementation of a strategy for developing a quality workforce is the key to promoting the high-quality development of China’s economy. Based on the panel data of 31 provinces on the Chinese mainland from 2013 to 2020, a spatial econometric model is used to explore the impact of the regional environment, regional heterogeneity and its spatial effect on the gathering of technological talent. The results show that: (1) The improvement of the regional innovation environment can significantly promote the gathering of technological talent in a region; (2) The regional innovation environment has an obvious regional effect on the gathering of technological talent, which is manifested in the strong promotion of the eastern and western regions, and an obvious siphon effect in the eastern region, but it is not the key factor affecting the gathering of technological talent in the central region; (3) The gathering of technological talent has a significant spatial effect among neighboring provinces. Therefore, improving the regional innovation environment, adapting measures to local conditions in different regions and strengthening economic cooperation among provinces have become the key to the rational allocation of technology talent resources

Optimization of Substrate Conformal Imprint Lithography (SCIL) and Etching for Nanostructure

The UV-SCIL fabrication process was developed and optimized to improve the quality of the nanostructures on the hard substrate transferred with substrate conformal imprint lithography (SCIL) technology. In particular, the key steps such as coating imprint resist, exposure time and etching time were investigated thoroughly. The experiment’s results illustrate that imprint resist could well serve as an etching mask for the dry etching process without oxygen plasma. The optimized etching condition and SCIL technology could also be used to transfer nanostructures on different substrates for metal nanostructured biosensors or nanophotonics

Does Regional Innovation Environment Have an Impact on the Gathering of Technological Talent? An Empirical Study Based on 31 Provinces in China

Driven by innovation, the implementation of a strategy for developing a quality workforce is the key to promoting the high-quality development of China’s economy. Based on the panel data of 31 provinces on the Chinese mainland from 2013 to 2020, a spatial econometric model is used to explore the impact of the regional environment, regional heterogeneity and its spatial effect on the gathering of technological talent. The results show that: (1) The improvement of the regional innovation environment can significantly promote the gathering of technological talent in a region; (2) The regional innovation environment has an obvious regional effect on the gathering of technological talent, which is manifested in the strong promotion of the eastern and western regions, and an obvious siphon effect in the eastern region, but it is not the key factor affecting the gathering of technological talent in the central region; (3) The gathering of technological talent has a significant spatial effect among neighboring provinces. Therefore, improving the regional innovation environment, adapting measures to local conditions in different regions and strengthening economic cooperation among provinces have become the key to the rational allocation of technology talent resources

Hyperspectral analysis of shale gas drilling in southern Huangling anticline

In this paper, the visible near infrared, short wave red, and thermal infrared spectral data and high-definition core images of three wells in Huangling anticline in Western Hubei are obtained by hylogger. Through comprehensive analysis, it can be seen that the thickness of Niutitang Formation is decreasing from west to East, However, the thickness of Doushantuo Formation is basically the same, ranging from 210m to 220m. Quartz, clay minerals, carbonate and limonite are the main minerals in Niutitang formation, while in Doushantuo Formation dolomite is the main mineral. Dolomite fracture is developed in this area, which is a favorable area for shale gas development

Effect of Fe3O4 nanoparticles on space charge distribution in propylene carbonate under impulse voltage

Addition of nanoparticles of the ferromagnetic material Fe3O4 can increase the positive impulse breakdown voltage of propylene carbonate by 11.65%. To further investigate the effect of ferromagnetic nanoparticles on the space charge distribution in the discharge process, the present work set up a Kerr electro-optic field mapping measurement system using an array photodetector to carry out time-continuous measurement of the electric field and space charge distribution in propylene carbonate before and after modification. Test results show that fast electrons can be captured by Fe3O4 nanoparticles and converted into relatively slow, negatively charged particles, inhibiting the generation and transportation of the space charge, especially the negative space charge

Pursuit Path Planning for Multiple Unmanned Ground Vehicles Based on Deep Reinforcement Learning

Path planning plays a crucial role in the execution of pursuit tasks for multiple unmanned ground vehicles (multi-UGVs). Although existing popular path-planning methods can achieve the pursuit goals, they suffer from some drawbacks such as long computation time and excessive path inflection points. To address these issues, this paper combines gradient descent and deep reinforcement learning (DRL) to solve the problem of excessive path inflection points from a path-smoothing perspective. In addition, the prioritized experience replay (PER) method is incorporated to enhance the learning efficiency of DRL. By doing so, the proposed model integrates PER, gradient descent, and a multiple-agent double deep Q-learning network (PER-GDMADDQN) to enable the path planning and obstacle avoidance capabilities of multi-UGVs. Experimental results demonstrate that the proposed PER-GDMADDQN yields superior performance in the pursuit problem of multi-UGVs, where the training speed and smoothness of the proposed method outperform other popular algorithms. As a result, the proposed method enables satisfactory path planning for multi-UGVs