Identification of driving factors of algal growth in the South-to-North Water Diversion Project by Transformer-based deep learning

Accurate and credible identification of the drivers of algal growth is essential for sustainable utilization and scientific management of freshwater. In this study, we developed a deep learning-based Transformer model, named Bloomformer-1, for end-to-end identification of the drivers of algal growth without the needing extensive a priori knowledge or prior experiments. The Middle Route of the South-to-North Water Diversion Project (MRP) was used as the study site to demonstrate that Bloomformer-1 exhibited more robust performance (with the highest R$^{2}$, 0.80 to 0.94, and the lowest RMSE, 0.22–0.43 ​μg/L) compared to four widely used traditional machine learning models, namely extra trees regression (ETR), gradient boosting regression tree (GBRT), support vector regression (SVR), and multiple linear regression (MLR). In addition, Bloomformer-1 had higher interpretability (including higher transferability and understandability) than the four traditional machine learning models, which meant that it was trustworthy and the results could be directly applied to real scenarios. Finally, it was determined that total phosphorus (TP) was the most important driver for the MRP, especially in Henan section of the canal, although total nitrogen (TN) had the highest effect on algal growth in the Hebei section. Based on these results, phosphorus loading controlling in the whole MRP was proposed as an algal control strategy

Transcription Factor NFAT5 Promotes Glioblastoma Cell-driven Angiogenesis via SBF2-AS1/miR-338-3p-Mediated EGFL7 Expression Change

Glioblastoma (GBM) is the most aggressive primary intracranial tumor of adults and confers a poor prognosis due to high vascularization. Hence anti-angiogenic therapy has become a promising strategy for GBM treatment. In this study, the transcription factor nuclear factor of activated T-cells 5 (NFAT5) was significantly elevated in glioma samples and GBM cell lines, and positively correlated with glioma WHO grades. Knockdown of NFAT5 inhibited GBM cell-driven angiogenesis. Furthermore, long non-coding RNA SBF2 antisense RNA 1 (SBF2-AS1) was upregulated in glioma samples and knockdown of SBF2-AS1 impaired GBM-induced angiogenesis. Downregulation of NFAT5 decreased SBF2-AS1 expression at transcriptional level. In addition, knockdown of SBF2-AS1 repressed GBM cell-driven angiogenesis via enhancing the inhibitory effect of miR-338-3p on EGF like domain multiple 7 (EGFL7). In vivo study demonstrated that the combination of NFAT5 knockdown and SBF2-AS1 knockdown produced the smallest xenograft volume and the lowest microvessel density. NFAT5/SBF2-AS1/miR-338-3p/EGFL7 pathway may provide novel targets for glioma anti-angiogenic treatment

Identification of driving factors of algal growth in the South-to-North Water Diversion Project by Transformer-based deep learning

Accurate and credible identification of the drivers of algal growth is essential for sustainable utilization and scientific management of freshwater. In this study, we developed a deep learning-based Transformer model, named Bloomformer-1, for end-to-end identification of the drivers of algal growth without the needing extensive a priori knowledge or prior experiments. The Middle Route of the South-to-North Water Diversion Project (MRP) was used as the study site to demonstrate that Bloomformer-1 exhibited more robust performance (with the highest R2, 0.80 to 0.94, and the lowest RMSE, 0.22–0.43 ​μg/L) compared to four widely used traditional machine learning models, namely extra trees regression (ETR), gradient boosting regression tree (GBRT), support vector regression (SVR), and multiple linear regression (MLR). In addition, Bloomformer-1 had higher interpretability (including higher transferability and understandability) than the four traditional machine learning models, which meant that it was trustworthy and the results could be directly applied to real scenarios. Finally, it was determined that total phosphorus (TP) was the most important driver for the MRP, especially in Henan section of the canal, although total nitrogen (TN) had the highest effect on algal growth in the Hebei section. Based on these results, phosphorus loading controlling in the whole MRP was proposed as an algal control strategy

Endothelial Monocyte-Activating Polypeptide-II Induces BNIP3-Mediated Mitophagy to Enhance Temozolomide Cytotoxicity of Glioma Stem Cells via Down-Regulating MiR-24-3p

Preliminary studies have shown that endothelial-monocyte-activating polypeptide-II (EMAP-II) and temozolomide (TMZ) alone can exert cytotoxic effects on glioma cells. This study explored whether EMAP-II can enhance the cytotoxic effects of TMZ on glioma stem cells (GSCs) and the possible mechanisms associated with Bcl-2/adenovirus E1B 19 kDa protein-interacting protein 3 (BNIP3)-mediated mitophagy facilitated by miR-24-3p regulation. The combination of TMZ and EMAP-II significantly inhibited GSCs viability, migration, and invasion, resulting in upregulation of the autophagy biomarker microtubule-associated protein one light chain 3 (LC3)-II/I but down-regulation of the proteins P62, TOMM 20 and CYPD, changes indicative of the occurrence of mitophagy. BNIP3 expression increased significantly in GSCs after treatment with the combination of TMZ and EMAP-II. BNIP3 overexpression strengthened the cytotoxic effects of EMAP-II and TMZ by inducing mitophagy. The combination of EMAP-II and TMZ decreased the expression of miR-24-3p, whose target gene was BNIP3. MiR-24-3p inhibited mitophagy and promoted proliferation, migration and invasion by down-regulating BNIP3 in GSCs. Furthermore, nude mice subjected to miR-24-3p silencing combined with EMAP-II and TMZ treatment displayed the smallest tumors and the longest survival rate. According to the above results, we concluded that EMAP-II enhanced the cytotoxic effects of TMZ on GSCs' proliferation, migration and invasion both in vitro and in vivo

Linc00152 promotes malignant progression of glioma stem cells by regulating miR-103a-3p/FEZF1/CDC25A pathway

Abstract Background Glioma is one of the most frequent intracranial malignant tumors. LncRNAs have been identified as new modulators in the origination and progression of glioma. Methods Quantitative real-time PCR were conducted to evaluate the expression of linc00152 and miRNA-103a-3p in glioma tissues and cells. Western blot were used to determine the expression of FEZF1 and CDC25A in glioma tissues and cells. Stable knockdown of linc00152 or over-expression of miR-103a-3p in glioma stem cells (GSCs) were established to explore the function of linc00152 and miR-103a-3p in GSCs. Further, luciferase reports were used to investigate the correlation between linc00152 and miR-103a-3p. Cell Counting Kit-8, transwell assays, and flow cytometry were used to investigate the function of linc00152 and miR-103a-3p in GSC malignant biological behaviors. ChIP assays were employed to ascertain the correlations between FEZF1 and CDC25A. Results Linc00152 was up-regulated in glioma tissues as well as in GSCs. Knockdown of linc00152 inhibited cell proliferation, migration and invasion, while promoted GSC apoptosis. Linc00152 regulated the malignant behavior of GSCs by binding to miR-103a-3p, which functions as a tumor suppressor. In addition, knockdown of linc00152 down-regulated forebrain embryonic zinc finger protein 1 (FEZF1), a direct target of miR-103a-3p which played an oncogenic role in GSCs. FEZF1 elevated promoter activities and up-regulated expression of the oncogenic gene cell division cycle 25A (CDC25A). CDC25A over-expression activated the PI3K/AKT pathways, which regulated the malignant behavior of GSCs. Conclusions Linc00152/miR-103a-3p/FEZF1/CDC25A axis plays a novel role in regulating the malignant behavior of GSCs, which may be a new potential therapeutic strategy for glioma therapy

Additional file 1 of RETRACTED ARTICLE: Linc00152 promotes malignant progression of glioma stem cells by regulating miR-103a-3p/FEZF1/CDC25A pathway

Isolation and identification of GSCs. A. a, c: Cells grew into spheres in serum-free medium. b, d: Spheres generated again from a single cell. B. Individual undifferentiated GSCs-87 and GSCs-251 stained for Nestin (green) and CD133 (red) by immunofluorescence analysis. C. Cell spheres were differentiated and then stained for GFAP (green) and β-tubulin III (red) by immunofluorescence analysis. Nuclei (blue) were labeled with DAPI. Images are representative of independent experiments (n = 5). Scale bars represent 20 μm. (TIFF 35029 kb