MAPK1 promotes the metastasis and invasion of gastric cancer as a bidirectional transcription factor

Background: The Mitogen-activated protein kinase 1 (MAPK1) has both independent functions of phosphorylating histones as a kinase and directly binding the promoter regions of genes to regulate gene expression as a transcription factor. Previous studies have identified elevated expression of MAPK1 in human gastric cancer, which is associated with its role as a kinase, facilitating the migration and invasion of gastric cancer cells. However, how MAPK1 binds to its target genes as a transcription factor and whether it modulates related gene expressions in gastric cancer remains unclear. Results: Here, we integrated biochemical assays (protein interactions and chromatin immunoprecipitation (ChIP)), cellular analysis assays (cell proliferation and migration), RNA sequencing, ChIP sequencing, and clinical analysis to investigate the potential genomic recognition patterns of MAPK1 in a human gastric adenocarcinoma cell-line (AGS) and to uncover its regulatory effect on gastric cancer progression. We confirmed that MAPK1 promotes AGS cells invasion and migration by regulating the target genes in different directions, up-regulating seven target genes (KRT13, KRT6A, KRT81, MYH15, STARD4, SYTL4, and TMEM267) and down-regulating one gene (FGG). Among them, five genes (FGG, MYH15, STARD4, SYTL4, and TMEM267) were first associated with cancer procession, while the other three (KRT81, KRT6A, and KRT13) have previously been confirmed to be related to cancer metastasis and migration. Conclusion: Our data showed that MAPK1 can bind to the promoter regions of these target genes to control their transcription as a bidirectional transcription factor, promoting AGS cell motility and invasion. Our research has expanded the understanding of the regulatory roles of MAPK1, enriched our knowledge of transcription factors, and provided novel candidates for cancer therapeutics

Operating Conditions of Hollow Fiber Supported Liquid Membrane for Phenol Extraction from Coal Gasification Wastewater

The extraction and recycling of phenol from high concentration coal gasification wastewater has been studied using polypropylene (PP) hollow fiber membrane and polyvinylidene fluoride (PVDF) hollow fiber membrane as liquid membrane support, the mixture of tributyl phosphate (TBP) and kerosene as liquid membrane phase, and sodium hydroxide as stripping agent in the process of extraction. The experiments investigated the effect of the operating conditions of the hollow fiber supported liquid membrane, such as aqueous phase temperature and the connection forms of membrane modules, on the extraction efficiency of phenol from high concentration coal gasification wastewater. The conclusions obtained from lab scale experiments provided guidance for scale-up experiments. So, in the scale-up experiments, three membrane modules connected in parallel, then three membrane modules connected in series were used to increase the treatment capacity and improve the treatment effect, under the operating conditions of wastewater temperature 20 ˚C, PH 7.5~8.1, flow rate 100 L/h and the concentration of stripping phase 0.1 mol/L, stripping phase flow rate 50 L/h, the extraction efficiency of the PP-TBP supported liquid membrane system was 87.02% and the phenol concentration of effluent was 218.14mg/L. And the phenol concentration of effluent met the requirements of further biodegradation treatment

Triptolide Inhibits the Proliferation of Prostate Cancer Cells and Down-Regulates SUMO-Specific Protease 1 Expression

Recently, traditional Chinese medicine and medicinal herbs have attracted more attentions worldwide for its anti-tumor efficacy. Celastrol and Triptolide, two active components extracted from the Chinese herb Tripterygium wilfordii Hook F (known as Lei Gong Teng or Thunder of God Vine), have shown anti-tumor effects. Celastrol was identified as a natural 26 s proteasome inhibitor which promotes cell apoptosis and inhibits tumor growth. The effect and mechanism of Triptolide on prostate cancer (PCa) is not well studied. Here we demonstrated that Triptolide, more potent than Celastrol, inhibited cell growth and induced cell death in LNCaP and PC-3 cell lines. Triptolide also significantly inhibited the xenografted PC-3 tumor growth in nude mice. Moreover, Triptolide induced PCa cell apoptosis through caspases activation and PARP cleavage. Unbalance between SUMOylation and deSUMOylation was reported to play an important role in PCa progression. SUMO-specific protease 1 (SENP1) was thought to be a potential marker and therapeutical target of PCa. Importantly, we observed that Triptolide down-regulated SENP1 expression in both mRNA and protein levels in dose-dependent and time-dependent manners, resulting in an enhanced cellular SUMOylation in PCa cells. Meanwhile, Triptolide decreased AR and c-Jun expression at similar manners, and suppressed AR and c-Jun transcription activity. Furthermore, knockdown or ectopic SENP1, c-Jun and AR expression in PCa cells inhibited the Triptolide anti-PCa effects. Taken together, our data suggest that Triptolide is a natural compound with potential therapeutic value for PCa. Its anti-tumor activity may be attributed to mechanisms involving down-regulation of SENP1 that restores SUMOylation and deSUMOyaltion balance and negative regulation of AR and c-Jun expression that inhibits the AR and c-Jun mediated transcription in PCa

Mental Health Question and Answering System Based on Bert Model and Knowledge Graph Technology

With the development and progress of society, people are facing increasing pressure. The emergence of this phenomenon has led to a rapid increase in the incidence of mental illness. In order to deal with this phenomenon, this paper proposes a system of question and answering on the basic knowledge of mental health (MHQ&A) by using deep learning retrieval technology and knowledge graph technology. The system MHQ&A is designed mainly for the general public, to answer the basic knowledge of mental health, especially the field of depression. First of all, the basic and the professional question and answer data about mental health were respectively obtained by the reptilian bot from the "IASK"website knowledge and the "Dr. Dingxiang"website. Then, the questions and answers obtained through the crawler are made into a Question and Answering Knowledge Graph of Basic Health Knowledge in the mental health field, which is combined with semantic data of antidepressants and the semantic data of depression papers. Finally, a set of template matching rules is designed to determine the type of problem of users. If the questions are about the professional knowledge of medicine or thesis, the reasoning template will be used to reason and search the answer in the "Question and Answering Knowledge Graph of Basic Health Knowledge in the Mental Health Field". If the questions are about other basic knowledge in the field of mental health, the BERT model is used to vectorize the questions of users, and the matching questions and corresponding answers in the MHQ&A are found through cosine similarity calculation. Through the test of system accuracy, it is proved that the system can effectively combine deep learning technology and knowledge

Analysis of sentiment changes in online messages of depression patients before and during the COVID-19 epidemic based on BERT+BiLSTM

With the development of the Internet, more and more people prefer to confide their sentiments in the virtual world, especially those with depression. The social media where people with depression collectively leave messages is called the “Tree Hole”. The purpose of this article is to support the “Tree Hole” rescue volunteers to help patients with depression, especially after the outbreak of COVID-19 and other major events, to guide the crisis intervention of patients with depression. Based on the message data of “Tree Hole” named “Zou Fan”, this paper used a deep learning model and sentiment scoring algorithm to analyze the fluctuation characteristics sentiment of user’s message in different time dimensions. Through detailed investigation of the research results, we found that the number of “Tree Hole” messages in multiple time dimensions is positively correlated to emotion. The longer the “Tree Hole” is formed, the more negative the emotion is, and the outbreak of COVID-19 and other major events have obvious effects on the emotion of the messages. In order to improve the efficiency of “Tree Hole” rescue, volunteers should focus on the long-formed “Tree Hole” and the user groups that are active in the early morning. This research is of great significance for the emotional guidance of online mental health patients, especially the crisis intervention for depression patients after the outbreak of COVID-19 and other major events

Automatic Detection and Classification of Road, Car, and Pedestrian Using Binocular Cameras in Traffic Scenes with a Common Framework

In order to solve the problems of traffic object detection, fuzzification, and simplification in real traffic environment, an automatic detection and classification algorithm for roads, vehicles, and pedestrians with multiple traffic objects under the same framework is proposed. We construct the final V view through a considerate U-V view method, which determines the location of the horizon and the initial contour of the road. Road detection results are obtained through error label reclassification, omitting point reassignment, and so an. We propose a peripheral envelope algorithm to determine sources of vehicles and pedestrians on the road. The initial segmentation results are determined by the regional growth of the source point through the minimum neighbor similarity algorithm. Vehicle detection results on the road are confirmed by combining disparity and color energy minimum algorithms with the object window aspect ratio threshold method. A method of multifeature fusion is presented to obtain the pedestrian target area, and the pedestrian detection results on the road are accurately segmented by combining the disparity neighbor similarity and the minimum energy algorithm. The algorithm is tested in three datasets of Enpeda, KITTI, and Daimler; then, the corresponding results prove the efficiency and accuracy of the proposed approach. Meanwhile, the real-time analysis of the algorithm is performed, and the average time efficiency is 13 pfs, which can realize the real-time performance of the detection process

Use of glucocorticoids in patients with COPD exacerbations in China: a retrospective observational study

Background: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are common in patients with underlying moderate to severe COPD and are associated with increased health and economic burden. International and Chinese guidelines recommend using glucocorticoids for the management of AECOPD because glucocorticoid therapy has been shown to benefit clinical outcomes. However, only scant data are available for current status of glucocorticoid therapy in hospitalized AECOPD patients in China. The aim of the study was to identify current use of glucocorticoids for the treatment of AECOPD in China. Methods: This retrospective, multicenter, noninterventional study evaluated the treatment pattern of AECOPD in patients hospitalized from January 2014 to September 2014 at 43 sites (41 tertiary hospitals and two secondary hospitals) in China. The endpoints of the study were the percentage of patients receiving glucocorticoids by different routes of administration, doses and duration, mortality, and the mean length of hospitalization. Results: A total of 4569 patients (90.17%) received glucocorticoids for AECOPD treatment. A combination of nebulized and systemic route was most frequently used (40.51%), followed by using nebulized route alone (38.00%), systemic route alone (15.45%), and inhaled route other than nebulization (6.04%). Furthermore, the most commonly prescribed glucocorticoids of the nebulized, intravenous, inhaled (other than nebulized) and oral route was budesonide (69.4%), methylprednisolone sodium succinate (45.31%), fluticasone propionate (19.54%), and prednisone acetate (11.90%), respectively. The in-hospital mortality rate was 1.24% and the mean length of hospitalization was 12.22 ± 6.20 days (± SD). Conclusions: Our study was the first study of the treatment pattern of glucocorticoids in the management of hospitalized AECOPD patients in China. Data indicates that there is a gap in the implementation of international guidelines for the treatment of AECOPD in China. Further studies are warranted to clarify the appropriate glucocorticoids strategy for the management of AECOPD to determine the optimal route of administration, dose and duration, and resulting clinical outcomes