Key Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha, Hunan, China.
National Research Center of Engineering Technology for Utilization of Functional Ingredients from Botanicals, Collaborative Innovation Centre of Utilisation of Functional Ingredients from Botanicals, Hunan Agricultural University, Changsha, Hunan, China.
Key Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha, Hunan, China.
National Research Center of Engineering Technology for Utilization of Functional Ingredients from Botanicals, Collaborative Innovation Centre of Utilisation of Functional Ingredients from Botanicals, Hunan Agricultural University, Changsha, Hunan, China.
Key Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha, Hunan, China.
National Research Center of Engineering Technology for Utilization of Functional Ingredients from Botanicals, Collaborative Innovation Centre of Utilisation of Functional Ingredients from Botanicals, Hunan Agricultural University, Changsha, Hunan, China.
Key Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha, Hunan, China.
National Research Center of Engineering Technology for Utilization of Functional Ingredients from Botanicals, Collaborative Innovation Centre of Utilisation of Functional Ingredients from Botanicals, Hunan Agricultural University, Changsha, Hunan, China.
Key Laboratory of Tea Science of Ministry of Education, Hunan Agricultural University, Changsha, Hunan, China.
National Research Center of Engineering Technology for Utilization of Functional Ingredients from Botanicals, Collaborative Innovation Centre of Utilisation of Functional Ingredients from Botanicals, Hunan Agricultural University, Changsha, Hunan, China.
Chemistry Unit, Department of Pharmacology, Animal Physiology and Physiological Chemistry, Faculty of Veterinary Medicine, Students Campus, Trakia University, 6000 Stara Zagora, Bulgaria.
Chemistry Unit, Department of Pharmacology, Animal Physiology and Physiological Chemistry, Faculty of Veterinary Medicine, Students Campus, Trakia University, 6000 Stara Zagora, Bulgaria.
Breast cancer (BC) is among the most common cancers worldwide. Machine learning-based radiomics model could predict axillary lymph node metastasis (ALNM) of BC accurately....
The purpose is to develop a machine learning model to predict ALNM of BC by focusing on the radiomics features of axillary lymphatic node (ALN)....
A group of 398 BC patients with 800 ALNs were retrospectively collected. A set of patient characteristics were obtained to form clinical factors. Three hundred and twenty-six radiomics features were e...
Among the 800 cases of ALNs, there were 388 cases of positive metastasis (48.50%) and 412 cases of negative metastasis (51.50%). The baseline clinical model achieved the performance with an AUC = 0.89...
Combinations of feature selection methods and machine learning-based classification algorithms can develop promising predictive models to predict ALNM in BC using CECT features. The combined model of ...
Endothelial-mesenchymal transition (EndoMT) is an emerging adaptive process that modulates lymphatic endothelial function to drive aberrant lymphatic vascularization in the tumour microenvironment (TM...
Immunofluorescent staining of α-SMA, LYVE-1 and DAPI were examined in primary tumour samples obtained from 57 CSCC patients. Assessment of cytokines secreted by CAFs and normal fibroblasts (NFs) was p...
CAF-derived PAI-1 promoted the EndoMT of LECs in CSCC. LECs undergoing EndoMT could initiate tumour neolymphangiogenesis that facilitated cancer cell intravasation/extravasation, which in turn promote...
Our data indicate that CAF-derived PAI-1 acts as an important neolymphangiogenesis-initiating molecular during CSCC progression through modulating the EndoMT of LECs, resulting in promotion of metasta...
Lymphangiogenesis in tumors provides an auxiliary route for cancer cell invasion to drainage lymph nodes, facilitating the development of lymphatic metastasis (LM). However, the mechanisms governing t...
Cellular senescence-the irreversible cell cycle arrest driven by a variety of mechanisms and, more specifically, the senescence-associated secretory phenotype (SASP)-is an important area of research i...
The natural history of advanced malignant melanoma demonstrates that, in most cases, widespread tumor dissemination is preceded by regional metastases involving tumor-draining lymph nodes [sentinel ly...
Gastric cancer (GC) is a malignant tumor with a high mortality rate, and lymphatic metastasis is the main mode of GC metastasis. The nuclear transcriptional regulatory protein SATB1 has been confirmed...
Epithelial-mesenchymal transition (EMT) is known as the pivotal process of GC metastasis. To evaluate the relationship between SATB1 and EMT in GC metastasis, the immunohistochemical method was used t...
Abnormal positive expression of SATB1 protein in paraffin-embedded tumor tissues was positively correlated with local invasion, lymph node metastasis, and TNM staging in gastric cancer. There was a st...
The GC patients with overexpression of SATB1 tended to have advanced stage and lymph node metastasis. SATB1 was positively correlated with EMT in Gastric Cancer....
Liver and lymph node sinusoidal endothelial cell C-type lectin (LSECtin) plays an important regulatory role in a variety of diseases, including tumors. However, the underlying mechanism of LSECtin in ...
This study aims to predict the lymphatic metastasis in Ewing's sarcoma (ES) patients by nomogram. The risk of lymphatic metastasis in patients with ES was predicted by the built model, which provided ...
A total of 929 patients diagnosed with ES were enrolled from the year of 2010 to 2016 in the Surveillance, Epidemiology, and End Results (SEER) database. The nomogram was established to determine pred...
In this study, the nomogram was established based on six significant factors (survival time, race, T stage, M stage, surgery, and lung metastasis), which were identified for lymphatic metastasis in ES...
In this study, we constructed and developed a nomogram with risk factors to predict lymphatic metastasis in ES patients and validated accuracy of itself. We found T stage (Tx OR = 2.540, 95%CI = 1.433...
The design of nanomedicine for cancer therapy, especially the treatment of tumor metastasis has received great attention. Proteasome inhibition is accepted as a new strategy for cancer therapy. Despit...
Lymphatic metastasis (LM) emerges as an independent prognostic marker for hypopharyngeal squamous cell carcinoma (HSPSCC), chiefly contributing to treatment inefficacy. This study aimed to scrutinize ...
In a preceding investigation, HSP90AA1, a differential gene, was discovered through transcriptome sequencing of HPSCC tissues, considering both the presence and absence of LM. Validation of HSP90AA1 e...
HSP90AA1 is substantially up-regulated in HPSCC with LM and is identified as an independent prognostic risk determinant. The down-regulation of HSP90AA1 can achieve inhibition of tumor cell proliferat...
HSP90AA1, by controlling EMT, can foster LM in HPSCC.This finding sets the foundation for delving into new therapeutic targets for HPSCC....
