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| 1 | Tumor-associated macrophages in osteosarcoma显示文摘Osteosarcoma(OS)is the most common primary bone tumor in children and adolescents.It is an aggressive tumor with a tendency to spread to the lung,which is the most common site of metastasis.Patients with advanced OS with metastases have poor prognoses despite the application of chemotherapy,thus highlighting the need for novel therapeutic targets.The tumor microenvironment(TME)of OS is confirmed to be essential for and supportive of tumor growth and dissemination.The immune component of the OS microenvironment is mainly composed of tumor-associated macrophages(TAMs).In OS,TAMs promote tumor growth and angiogenesis and upregulate the cancer stem cell-like phenotype.However,TAMs inhibit the metastasis of OS.Therefore,much attention has been paid to investigating the mechanism of TAMs in OS development and the progression of immunotherapy for OS.In this article,we aim to summarize the roles of TAMs in OS and the major findings on the application of TAMs in OS treatment. | Yi ZHAO Benzheng ZHANG Qianqian ZHANG Xiaowei MA Helin FENG | 2021 | Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)2021，22，11： | 1 |
| 2 | Devel- opment of Pineapple Microsatellite Markers and 6ermplasm Genetic Diversity Analysis 显示文摘 | Suping Feng Helin Tong You Chen | 2013 | BioMed Research International2013，，2013： | 1 |
| 3 | Anomaly Detection of Multivariate Time Series Based on Metric Learning显示文摘Most of the current methods for anomaly detection in time series are unsupervised.However,unsupervised learning assumes the distribution of the data and cannot obtain satisfactory results in some scenarios.In this paper,we design a semisupervised time series anomaly detection algorithm based on metric learning.The algorithm model mines the features in the time series from the perspectives of the time domain and frequency domain.Furthermore,we design a loss function for anomaly detection.Different from the two-class loss function,in the scenario of the loss function we designed,the normal data will be clustered and distributed in the embedding space,and the abnormal data will be far from the normal data distribution.Furthermore,we extend our designed metric learning model to a semisupervised learning model,extending the labeled dataset with the unlabeled dataset by setting different confidence levels.We conduct experiments on different public datasets and compare them with commonly used time series anomaly detection algorithms.The results show that our model has a good effect.At the same time the semisupervised setting does improve the accuracy of model detection. | Hongkai Wang Jun Feng Liangying Peng Sichen Pan Shuai Zhao Helin Jin | 2022 | 国际计算机前沿大会会议论文集2022，，1： | 0 |
| 4 | Effects of soil potassium levels on dry matter and nutrient accumulation and distribution in cotton显示文摘Background Potassium(K)is an essential nutrient for plant growth and development.However,plant fertilization ignoring the soil K level is very likely to cause excessive fertilizer use,and further arouse a series of side effects.This study investigated the response of cotton growth to different soil K levels and the uptake of major nutrients,aiming to evaluate the appropriate K supply level for cotton growth.Using a random block design with 6 soil K levels,we conducted 18 micro-zones field experiments over two continuous years.The soil available K concentration of each treatment was K1(99.77-100.90 mg·kg^(-1)),K2(110.90-111.26 mg·kg^(-1)),K3(123.48-128.88 mg·kg^(-1)),K4(140.13-145.10 mg·kg^(-1)),K5(154.43-155.38 mg·kg^(-1)),and K6(165.77-168.75 mg·kg^(-1)).Cotton nutrient contents,soil nutrient contents,accumulation and distribution of dry matter in cotton were determined,and the relationships between K content in soil and plants and dry matter accumulation were analyzed.Results The soil K content had a significantly positive relationship with dry matter and K accumulation in cotton plants.There were significant differences in dry matter accumulation,single-plant seed cotton yield,mineral nutrient uptake and the proportion of K accumulation in reproductive organs among different soil K levels.The results showed that there was significant difference between K4 and lower K level treatments(K1 and K2),but no significant difference between K4 and higher K level treatments(K5 and K6)in dry matter,single-plant seed cotton yield,or accumulation,distribution and seed cotton production efficiency of N,P and K.Conclusion The soil K level of K4 was able to provide sufficient K for cotton growth in our experiment.Therefore,when the soil K level reached 140.13 mg·kg^(-1),further increasing the soil K concentration no longer had a significant positive effect on cotton growth. | Jingjing SHAO Helin DONG Yinan JIN Pengcheng LI Miao SUN Weina FENG Cangsong ZHENG | 2023 | Journal of Cotton Research2023，6，2： | 0 |
| 5 | Leptin promotes proliferation and invasion of osteosarcoma cells by upregulating the expression of SIRT1显示文摘Osteosarcoma(OS)is a primary high-grade malignant bone neoplasm,and the prognosis ofOS remains poor due to early metastasis.Leptin plays an essential role in tumorigenesis,but the role of leptin in the development of OS is still not fully understood.In this study,we used a human osteosarcomaMG-63 cell line as an experimentalmodel.MG-63 cells were treated with leptin,and cell proliferation,apoptosis,adhesion,invasion,and gene expression,were evaluated.The results showed that leptin promoted proliferation,decreased adhesion,suppressed apoptosis,and promoted invasion,of MG-63 cells.Moreover,the expression of SIRT1 was upregulated in MG-63 cells exposed to leptin.Furthermore,MMP-2,8,and 9 were significantly upregulated by SIRT1,while SIRT1 knockdown inhibited the proliferation and invasion of MG-63 cells.In conclusion,our results suggest that leptin promotes OS cell proliferation and invasion by inducing the expression of SIRT1. | HELIN FENG XIAOCHONG ZHANG QIANQIAN ZHANG ZE LI LILI ZHAO | 2020 | BIOCELL2020，44，3： | 0 |
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