Diaqua­(2,9-dimethyl-1,10-phenanthroline-κ2 N,N′)(4-hydroxy­benzoato-κ2 O,O′)cobalt(II) nitrate dihydrate

In the title compound, [Co(C7H5O3)(C14H12N2)(H2O)2]NO3·2H2O, the CoII ion is six-coordinated by two N atoms of a 2,9-dimethyl-1,10-phenanthroline (dmphen) ligand, two carboxyl­ate O atoms of one 4-hydroxy­benzoate anion and two O atoms of two water mol­ecules, in a distorted octa­hedral environment; the two water mol­ecules occupy the apical positions. In the crystal structure, the ionic units and water mol­ecules are linked through O—H⋯O hydrogen bonds, leading to the formation of a three-dimensional network. In addition, π–π inter­actions between a pyridine ring of the dmphen ligand and the benzene ring of the hydroxy­benzoate anion [centroid–centroid separation = 3.6861 (3) Å] are observed

Identification of pyroptosis-related subtypes and establishment of prognostic model and immune characteristics in asthma

BackgroundAlthough studies have shown that cell pyroptosis is involved in the progression of asthma, a systematic analysis of the clinical significance of pyroptosis-related genes (PRGs) cooperating with immune cells in asthma patients is still lacking.MethodsTranscriptome sequencing datasets from patients with different disease courses were used to screen pyroptosis-related differentially expressed genes and perform biological function analysis. Clustering based on K-means unsupervised clustering method is performed to identify pyroptosis-related subtypes in asthma and explore biological functional characteristics of poorly controlled subtypes. Diagnostic markers between subtypes were screened and validated using an asthma mouse model. The infiltration of immune cells in airway epithelium was evaluated based on CIBERSORT, and the correlation between diagnostic markers and immune cells was analyzed. Finally, a risk prediction model was established and experimentally verified using differentially expressed genes between pyroptosis subtypes in combination with asthma control. The cMAP database and molecular docking were utilized to predict potential therapeutic drugs.ResultsNineteen differentially expressed PRGs and two subtypes were identified between patients with mild-to-moderate and severe asthma conditions. Significant differences were observed in asthma control and FEV1 reversibility between the two subtypes. Poor control subtypes were closely related to glucocorticoid resistance and airway remodeling. BNIP3 was identified as a diagnostic marker and associated with immune cell infiltration such as, M2 macrophages. The risk prediction model containing four genes has accurate classification efficiency and prediction value. Small molecules obtained from the cMAP database that may have therapeutic effects on asthma are mainly DPP4 inhibitors.ConclusionPyroptosis and its mediated immune phenotype are crucial in the occurrence, development, and prognosis of asthma. The predictive models and drugs developed on the basis of PRGs may provide new solutions for the management of asthma

Effects of K-dopant on structure and activity of KMn/Al2O3 catalysts for CO oxidation: Experimental evidence and DFT calculation

KMn/Al2O3 catalysts with different K:Mn molar ratios were synthesized by a facile impregnation method and attempted for CO oxidation. The correlation in between potassium-dopant amount and the structure/catalytic activity of KMn/Al2O3 catalysts were investigated. Doping small amount of potassium (K:Mn mole ratio less than 1:10) to Mn/Al2O3 catalyst efficiently enhanced the catalytic activity of Mn/Al2O3 catalyst. We found that the K1Mn10/Al2O3 catalyst exhibited the best CO oxidation activity with the TOF of 1.5 x 10(-3) s(-1) for 100% CO conversion at 260 degrees C, which is 50 degrees C lower than that on Mn/Al2O3 catalyst. However, excessive amounts of potassium led to beta-to-alpha-MnO2 phase transformation and poor catalytic performance. DFT calculations combined with multiple characterization techniques such as X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), O-2 temperature-programmed desorption (O-2-TPD) and hydrogen temperature-programmed reduction (H-2-TPR) were performed to provide a deep insight into the K-doping effect. The results suggested that the addition of an appropriate amount of potassium to Mn/Al2O3 catalyst improved the dispersion of manganese oxide, the mobility and reactivity of surface lattice oxygen, thus significantly improved the catalyst activity. (C) 2016 Published by Elsevier B.V

Natural Antioxidants Improve the Vulnerability of Cardiomyocytes and Vascular Endothelial Cells under Stress Conditions: A Focus on Mitochondrial Quality Control

Cardiovascular disease has become one of the main causes of human death. In addition, many cardiovascular diseases are accompanied by a series of irreversible damages that lead to organ and vascular complications. In recent years, the potential therapeutic strategy of natural antioxidants in the treatment of cardiovascular diseases through mitochondrial quality control has received extensive attention. Mitochondria are the main site of energy metabolism in eukaryotic cells, including myocardial and vascular endothelial cells. Mitochondrial quality control processes ensure normal activities of mitochondria and cells by maintaining stable mitochondrial quantity and quality, thus protecting myocardial and endothelial cells against stress. Various stresses can affect mitochondrial morphology and function. Natural antioxidants extracted from plants and natural medicines are becoming increasingly common in the clinical treatment of diseases, especially in the treatment of cardiovascular diseases. Natural antioxidants can effectively protect myocardial and endothelial cells from stress-induced injury by regulating mitochondrial quality control, and their safety and effectiveness have been preliminarily verified. This review summarises the damage mechanisms of various stresses in cardiomyocytes and vascular endothelial cells and the mechanisms of natural antioxidants in improving the vulnerability of these cell types to stress by regulating mitochondrial quality control. This review is aimed at paving the way for novel treatments for cardiovascular diseases and the development of natural antioxidant drugs

IGFBP3 induces PD-L1 expression to promote glioblastoma immune evasion

Abstract Background Glioblastoma (GBM) characterized by immune escape is the most malignant primary brain tumors, which has strong immunosuppressive effect. Programmed death ligand-1 (PD-L1) is a recognized immunosuppressive member on the surface of tumor cells, and plays a crucial role in immune evasion of tumors. Actually, little is known about the regulation of PD-L1 expression in GBM. Insulin-like growth factor binding protein 3 (IGFBP3) is upregulated in GBM and is related to poor patient prognosis. However, it remains unclear whether IGFBP3 plays a role in the regulation of PD-L1 expression in GBM. Methods The role of IGFBP3 in the glioma immune microenvironment was investigated using the CIBERSORT algorithm. The correlation between IGFBP3 and PD-L1 expression was analyzed using TCGA and CGGA databases. QRT-PCR, immunoblotting and RNA-seq were used to examine the regulatory effect of IGFBP3 on PD-L1 expression. Co-culture assay, cell counting kit (CCK-8), qRT-PCR, ELISA and flow cytometry were performed to explore the function of IGFBP3 in inducing immunosuppression. The biological role of IGFBP3 was verified using immunohistochemical, immunofluorescence and mice orthotopic tumor model. Results In this study, we analyzed immune cells infiltration in gliomas and found that IGFBP3 may be associated with an immunosuppressive microenvironment. Then, by analyzing TCGA and CGGA databases, our results showed that IGFBP3 and PD-L1 expression were positively correlated in GBM patients, but not in LGG patients. In vitro experiments conducted on different GBM cell lines revealed that the overexpression of IGFBP3 led to an increase in PD-L1 expression, which was reversible upon knockdown IGFBP3. Mechanistically, IGFBP3 activated the JAK2/STAT3 signaling pathway, leading to an increase in PD-L1 expression. Additionally, co-culture experiments results showed IGFBP3 overexpression induced upregulation of PD-L1 expression promoted apoptosis in Jurkat cells, and this effect was blocked by IGFBP3 antibody and PDL-1 inhibitors. Importantly, in vivo experiments targeting IGFBP3 suppressed tumor growth and significantly prolonged the survival of mice. Conclusions This research demonstrated IGFBP3 is a novel regulator for PD-L1 expression in GBM, and identified a new mechanism by which IGFBP3 regulates immune evasion through PD-L1, suggesting that IGFBP3 may be a potential novel target for GBM therapy

Table2_Mechanistic studies of MALAT1 in respiratory diseases.DOCX

Background: The incidence of respiratory diseases and the respiratory disease mortality rate have increased in recent years. Recent studies have shown that long non-coding RNA (lncRNA) MALAT1 is involved in various respiratory diseases. In vascular endothelial and cancer cells, MALAT1 expression triggers various changes such as proinflammatory cytokine expression, cancer cell proliferation and metastasis, and increased endothelial cell permeability.Methods: In this review, we performed a relative concentration index (RCI) analysis of the lncRNA database to assess differences in MALAT1 expression in different cell lines and at different locations in the same cell, and summarize the molecular mechanisms of MALAT1 in the pathophysiology of respiratory diseases and its potential therapeutic application in these conditions.Results: MALAT1 plays an important regulatory role in lncRNA with a wide range of effects in respiratory diseases. The available evidence shows that MALAT1 plays an important role in the regulation of multiple respiratory diseases.Conclusion: MALAT1 is an important regulatory biomarker for respiratory disease. Targeting the regulation MALAT1 could have important applications for the future treatment of respiratory diseases.</p

Additional file 1 of IGFBP3 induces PD-L1 expression to promote glioblastoma immune evasion

Additional file 1: Table S1. qRT-PCR primers