Effect of Inflammation on the Process of Stroke Rehabilitation and Poststroke Depression

A considerable body of evidence has shown that inflammation plays an important role in the process of stroke rehabilitation and development of poststroke depression (PSD). However, the specific molecular and cellular mechanisms involved remain unclear. In this review, we summarize how neuroinflammation affects stroke rehabilitation and PSD. We mainly focus on the immune/inflammatory response, involving astrocytes, microglia, monocyte-derived macrophages, cytokines (tumor necrosis factor alpha, interleukin 1), and microRNAs (microRNA-124, microRNA 133b). This review provides new insights into the effect of inflammation on the process of stroke rehabilitation and PSD and potentially offer new therapeutic targets of stroke and PSD

Application of colony-stimulating factor 3 in determining the prognosis of high-grade gliomas based on magnetic resonance imaging radiomics

Rationale and objectives: Radiomics is a promising, non-invasive method for determining the prognosis of high-grade glioma (HGG). The connection between radiomics and the HGG prognostic biomarker is still insufficient. Materials and methods: In this study, we collected the pathological, clinical, RNA-sequencing, and enhanced MRI data of HGG from TCIA and TCGA databases. We characterized the prognostic value of CSF3. Kaplan–Meier (KM) analysis, univariate and multivariate Cox regression, subgroup analysis, Spearman analysis, and gene set variation analysis enrichment were used to elucidate the prognostic value of the CSF3 gene and the correlation between CSF3 and tumor features. We used CIBERSORT to analyze the correlation between CSF3 and cancer immune infiltrates. Logistic regression (LR) and support vector machine methods (SVM) were used to build the radiomics models for the prognosis prediction of HGG based on the expression of CSF3. Results: Based on the radiomics score calculated from LR model, 182 patients with HGG from TCGA database were divided into radiomics score (RS) high and low groups. CSF3 expression varied between tumor and normal group tissues. CSF3 expression was found to be a significant risk factor for survival outcomes. A positive association was found between CSF3 expression and immune infiltration. The radiomics model based on both LR and SVM methods showed high clinical practicability. Conclusion: The results showed that CSF3 has a prognostic value in HGG. The developed radiomics models can predict the expression of CSF3, and further validate the predictions of the radiomics models for HGG

MEK/ERK dependent activation of STAT1 mediates dasatinib-induced differentiation of acute myeloid leukemia.

Dasatinib (BMS-354825) is a FDA-approved multitargeted kinase inhibitor of BCR/ABL and Src kinases. It is now used in the treatment of chronic myelogenous leukemia (CML) with resistance or intolerance to prior therapies, including imatinib. Here we report a novel effect of dasatinib on inducing the differentiation of acute myeloid leukemia (AML) cells through MEK/ERK-dependent activation of signal transducer and activator of transcription 1 (STAT1). We found that dasatinib could induce the differentiation of AML cells as demonstrated by the expression of differentiation marker CD11b, G0/G1 phase arrest and decreased ratio of nucleus to cytoplasm. Of note, dasatinib induced robust phosphorylation of STAT1 both at Tyr701 and Ser727 as well as the redistribution of STAT1 from the cytoplasm to the nucleus, thus leading to the transcription of STAT1-targeted genes. Knocking down STAT1 expression by shRNA significantly attenuated dasatinib-induced differentiation, indicating an important role of STAT1 in myeloid maturation. We further found that dasatinib-induced activation of STAT1 was regulated by the MEK/ERK kinases. The phosporylation of MEK and ERK occurred rapidly upon dasatinib treatment and increased progressively as differentiation was induced. MEK inhibitors PD98059 and U0216 not only inhibited the phosphorylation of STAT1, but also abrogated dasatinib-induced myeloid differentiation, suggesting that MEK/ERK dependent phosphorylation of STAT1 might be indispensable for the differentiating effect of dasatinib in AML cells. Taken together, our study suggests that STAT1 is an important mediator in dasatinib-induced differentiation of AML cells, whose activation requires the activation of MEK/ERK cascades

Silencing of STAT1 expression by shRNA inhibits dasatinib-induced differentiation of HL60 cells.

<p>HL60 cells transduced with empty vector, Non-target shRNA or STAT1 shRNA (shSTAT1-1 and shSTAT1-2) were treated with dasatinib (10 µM) for 72 h. (A) STAT1 expression was detected by Western blotting. Band intensities were quantified using Quantity One 4.4.0 software (Bio-Rad) and then normalized to the amount of GAPDH in each sample. All samples were compared with the signal detected in Non-target shRNA transduced cells. The data are representative of three independent experiments. (B) NBT reduction assay was performed as described. The percentage of NBT-positive cells was calculated by counting at least 200 cells under a light microscope. Data presented are the mean ± SD of three independent experiments. *** P<.001 (C) CD11b expression was measured by flow cytometer. Data presented are the mean ± SD of three independent experiments. ** P<.01, * P<.05 (D) Cells were collected onto slides by cytospin, stained by Wright–Giemsa stain and observed under microscope. Original magnification, ×40. The data are representative of three independent experiments.</p

Dasatinib-induced AML differentiation requires MEK/ERK-dependent activation of STAT1.

<p>HL60 cells were treated with dasatinib (10 µM) in the presence of PD98059 (20 µM) for 72 h, and NB4 cells were treated with dasatinib (5 µM) in the presence of PD98059 (10 µM) for 48 h. HL60 and NB4 cells were pretreated with PD98059 for 1 h, and then incubated with dasatinb. (A) The percentages of CD11b expression cells were determined as described. Data presented are the mean ± SD of three independent experiments. (B) Cell cycle proportion was analyzed as described. Data presented are the mean ± SD of three independent experiments. *** P<.001, * P<.05. (C) and (D) The expression of p-MEK, p-ERK, p-STAT1(Y701) and p-STAT1(S727) as well as their total proteins in HL60 and NB4 cells were analyzed by Western blotting. The experiments were repeated three times and the data show the representative results.</p

Dasatinib enhances the phosphorylation of MEK/ERK cascades.

<p>HL60 cells were treated with dasatinib (10 µM) for the indicated times. The expressions of phosphorylated MEK, ERK, p38, JNK and AKT as well as their total proteins were analyzed by Western blotting. All the experiments were repeated three times and the data show the representative results.</p

Dasatinib induces activation of STAT1.

<p>HL60 cells were treated with dasatinib (10 µM) for the indicated times. (A) Whole cell lysates were analyzed by SDS-PAGE followed by Western blotting using specific antibodies. The experiments were repeated three times and the data show the representative results. (B) Representative fluorescence microphotographs showed a translocation of STAT1 from cytoplasm to nucleus. Original magnification, ×63. The results are representative of three independent experiments. (C) The expression of CXCL-10 and RIG-G and IRF-1 mRNA was determined by real-time quantitative PCR. The expression of GAPDH was used as the internal control gene. Shown are fold increases over untreated cells. Data presented are the mean ± SD of three independent experiments. *** P<.001, ** P<.01, * P<.05 versus untreated cells. (D) NB4 cells were treated with dasatinib (5 µM) for the indicated times. The level of p-STAT1 (Y701), p-STAT1 (S727), STAT1 and GAPDH proteins was determined by Western blotting analysis. The results are representative of three independent experiments.</p

Dasatinib induces differentiation of NB4 cells.

<p>NB4 cells were treated with different concentrations of dasatinib for the indicated times. (A) The percentages of CD11b expression cells were determined as described. Data presented are the mean ± SD of three independent experiments. *** P<.001, ** P<.01 versus vehicle treated cells. (B) Cell cycle proportion was analyzed as described. Data presented are the mean ± SD of three independent experiments. *** P<.001, ** P<.01, */# P<.05 versus vehicle treated cells. (C) HL60 cells were treated with dasatinib (10 µM) for 72 h and NB4 cells were treated with dasatinib (5 µM) for 48 h. Cells were collected and cytospined onto slides, then stained with Wright–Giemsa stain. Stained cells were observed under microscope (×40). The data are representative of three independent experiments.</p