The novel prolyl hydroxylase-2 inhibitor caffeic acid upregulates hypoxia inducible factor and protects against hypoxia

Background & aims: Hypoxia inducible factor (HIF) is a hypoxia-associated transcription factor that has a protective role against hypoxia-induced damage. Prolyl hydroxylase-2 (PHD2) is a dioxygenase enzyme that specifically hydroxylates HIF targeting it for degradation, therefore, inhibition of the PHD2 enzyme activity acts to upregulate HIF function. This study was to identify novel PHD2 inhibitors. Methods: An established fluorescence-based PHD2 activity assay was used for inhibitors screening. Western blot and quantitative real-time PCR was used to detect the protein and mRNA levels respectively. Further animal experiment was carried out. Results: Caffeic acid was screened and identified as a novel PHD2 inhibitor. Caffeic acid treated PC12 and SH-SY5Y neuronal cell lines stabilized endogenous HIF-1α protein levels and consequently increased mRNA levels of its downstream regulated genes VEGF and EPO. Caffeic acid treatment reduced hypoxia-induced cell apoptosis and promoted HIF/BNIP3-mediated mitophagy. Moreover, animal studies indicated that caffeic acid increased the level of HIF-1α protein and mRNA levels of VEGF and EPO in the brain of mice exposed to hypoxia. Conventional brain injury markers including malondialdehyde, lactic acid and lactate dehydrogenase in the caffeic acid treated mice were shown to be reduced to the levels of the control group. Conclusions: This study suggests that caffeic acid inhibits PHD2 enzyme activity which then activates the hypoxia-associated transcription factor HIF leading to a neuroprotective effect against hypoxia

Comprehensive characterization of endoplasmic reticulum stress in bladder cancer revealing the association with tumor immune microenvironment and prognosis

Background: This study constructs a molecular subtype and prognostic model of bladder cancer (BLCA) through endoplasmic reticulum stress (ERS) related genes, thus helping to clinically guide accurate treatment and prognostic assessment.Methods: The Bladder Cancer (BLCA) gene expression data was downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We clustered by ERS-related genes which obtained through GeneCards database, results in the establishment of a new molecular typing of bladder cancer. Further, we explored the characteristics of each typology in terms of immune microenvironment, mutations, and drug screening. By analyzing the ERS-related genes with univariate Cox, LASSO and multivariate Cox analyses, we also developed the four-gene signature, while validating the prognostic effect of the model in GSE32894 and GSE13507 cohorts. Finally, we evaluated the prognostic value of the clinical data in the high and low ERS score groups and constructed a prognostic score line graph by Nomogram.Results: We constructed four molecular subtypes (C1- C4) of bladder cancer, in which patients with C2 had a poor prognosis and those with C3 had a better prognosis. The C2 had a high degree of TP53 mutation, significant immune cell infiltration and high immune score. In contrast, C3 had a high degree of FGFR3 mutation, insignificant immune cell infiltration, and reduced immune checkpoint expression. After that, we built ERS-related risk signature to calculate ERS score, including ATP2A3, STIM2, VWF and P4HB. In the GSE32894 and GSE13507, the signature also had good predictive value for prognosis. In addition, ERS scores were shown to correlate well with various clinical features. Finally, we correlated the ERS clusters and ERS score. Patients with high ERS score were more likely to have the C2 phenotype, while patients with low ERS score were C3.Conclusion: In summary, we identified four novel molecular subtypes of BLCA by ERS-related genes which could provide some new insights into precision medicine. Prognostic models constructed from ERS-related genes can be used to predict clinical outcomes. Our study contributes to the study of personalized treatment and mechanisms of BLCA

Quick extraction of recycled sand morphology parameters based on deep learning and their effect on mortar property

Due to the limited application of the natural river sand in China, recycled sand (RS) has been considered as an important replacement of natural sand in sustainable construction. The morphology of recycled sand is critical to its effective application in mortar and concrete. An environmentally friendly approach is introduced in this work to improve the morphology of recycled sand during its crushing process. This paper presents a newly developed image acquisition device, which obtained 25,328 RS images to use as a dataset for the construction of a segmentation model based on deep learning technology with an automatic segmentation of RS characteristics. Evaluation indices including accuracy (ACC), Recall, intersection over union (IoU), and F1-score index are reaching up to 99.8%, 88.1%, 84.9% and 84.3%, respectively. RS morphological characteristics including the flat and elongation ratio (FER), angularity index (AI), roundness (R) are automatically extracted by the proposed model, and the predicted results agreed well with the experimental ones. Finally, the effect of FER of RS on mortar’s mechanical properties is investigated by a series of experiments. Results reveal that the flowability, flexural strength and compressive strength of mortar decreased invariably with the lower FER of sand

Cu-Doped Porous Carbon Derived from Heavy Metal-Contaminated Sewage Sludge for High-Performance Supercapacitor Electrode Materials

In this paper, we report a complete solution for enhanced sludge treatment involving the removal of toxic metal (Cu(II)) from waste waters, subsequent pyrolytic conversion of these sludge to Cu-doped porous carbon, and their application in energy storage systems. The morphology, composition, and pore structure of the resultant Cu-doped porous carbon could be readily modulated by varying the flocculation capacity of Cu(II). The results demonstrated that it exhibited outstanding performance for supercapacitor electrode applications. The Cu(II) removal efficiency has been evaluated and compared to the possible energy benefits. The flocculant dosage up to 200 mg·L−1 was an equilibrium point existing between environmental impact and energy, at which more than 99% Cu(II) removal efficiency was achieved, while the resulting annealed product showed a high specific capacity (389.9·F·g−1 at 1·A·g−1) and good cycling stability (4% loss after 2500 cycles) as an electrode material for supercapacitors