Cilostazol for Aneurysmal Subarachnoid Hemorrhage: An Updated Systematic Review and Meta-Analysis.

BACKGROUND AND PURPOSE: Delayed cerebral ischemia is a major cause of morbidity and mortality in patients with aneurysmal subarachnoid hemorrhage (aSAH). Cilostazol, a selective inhibitor of phosphodiesterase 3, was reported to reduce cerebral vasospasm and improve outcomes. We aimed to conduct an updated systematic review and meta-analysis of the efficacy and safety of cilostazol in aSAH. METHODS: We systematically searched PubMed, Embase, MEDLINE, and the Cochrane Library for articles published in English with the latest publishing time in August 2020. Articles reporting favorable outcome as the primary outcome and reporting severe angiographic vasospasm (aVS), symptomatic vasospasm (sVS), new cerebral infarction, or mortality as the secondary outcome were included in this review. Furthermore, we examined whether clinical outcomes were associated with the dosage of cilostazol (300 mg/day vs. 100-200 mg/day). RESULTS: Data from 405 patients in 4 randomized controlled trials (RCTs) and 461 patients in 4 observational studies (OSs) were included. In RCT studies, cilostazol was associated with significant favorable outcomes at discharge or 1 month (risk ratio [RR] 1.41, 95% confidence interval [CI] 1.01-1.97, p = 0.04) or 3 or 6 months (RR 1.16, 95% CI 1.05-1.28, p = 0.002). However, in OSs, no significant difference was indicated in favorable outcomes at discharge or 1 month (RR 1.22, 95% CI 0.94-1.60, p = 0.14) nor 3 or 6 months (RR 1.29, 95% CI 0.92-1.81, p = 0.14). The analyses found that cilostazol significantly reduced the incidences of severe aVS (RCT: RR 0.64, 95% CI 0.41-1.01, p = 0.05; OS: RR 0.61, 95% CI 0.43-0.88, p = 0.007), sVS (RCT: RR 0.46, 95% CI 0.31-0.70, p = 0.0002; OS: RR 0.38, 95% CI 0.21-0.68, p = 0.001), and new cerebral infarction (RCT: RR 0.40, 95% CI 0.24-0.67, p = 0.0005; OS: RR 0.38, 95% CI 0.23-0.64, p = 0.0002). However, no significant difference in mortality (RCT: RR 0.86, 95% CI 0.23-3.21, p = 0.82; OS: RR 0.16, 95% CI 0.02-1.24, p = 0.08) was found. In 3 OSs which reported different doses of cilostazol (300 mg/day vs. 100-200 mg/day) for aSAH, the 300-mg/day cilostazol groups showed decreased delayed cerebral infarction (RR 0.27, 95% CI 0.09-0.81, p = 0.02) but no significant difference in shunt-dependent hydrocephalus (RR 0.92, 95% CI 0.33-2.60, p = 0.88) or functional outcomes (RR 1.14, 95% CI 0.74-1.75, p = 0.56) compared with the 100-200 mg/day cilostazol groups. CONCLUSIONS: The meta-analyses suggest the credible efficacy and safety of cilostazol in treating aSAH. Furthermore, 300-mg/day cilostazol treatment appeared to be more effective than 100-200 mg/day treatment.

NLRP3 inflammasome mediates angiotensin II-induced islet ß cell apoptosis.

Elevation of angiotensin II (Ang II) in the serum of patients with diabetes is known to promote apoptosis of islet ß cells, but the underlying mechanism remains unclear. The aim of the present study was to explore the role of Nod-like receptor protein 3 (NLRP3) inflammasome in Ang II-induced apoptosis of pancreatic islet ß cells and investigate the possible underlying mechanism. The effect of Ang II on INS-1 cell (a rat insulinoma cell line) viability was detected by CCK-8 method. The cell apoptosis was detected by flow cytometry and western blot analysis. The effect of Ang II on the expressions of thioredoxin-interacting protein (TXNIP) and NLRP3 protein was detected by western blot analysis. The expression of TXNIP mRNA was detected by real-time polymerase chain reaction. The results showed that Ang II was able to reduce INS-1 cell viability and promote apoptosis and at the same time up-regulate the expressions of TXNIP and NLRP3 components. Ang II-induced apoptosis was inhibited after administration of the NLRP3 inhibitor MCC950, and TXNIP silencing could reduce the NLRP3 expression and apoptosis, while both effects of Ang II on TXNIP-NLRP3 and its apoptosis-inducing effect were inhibited by angiotensin II type I receptor (AT1R) blocker Telmisartan. Our results demonstrated that the TXNIP-NLRP3 inflammasome pathway mediated Ang II-induced INS-1 cell apoptosis and might hopefully become a novel target for the treatment of diabetes mellitus.

[Angiotensin II promotes the expression of TXNIP through angiotensin II type 1 receptor in islet ß cells].

This study investigated the effect of angiotensin II (Ang II) on apoptosis and thioredoxin-interacting protein (TXNIP) expression in INS-1 islet cells and the underlying mechanism. INS-1 cells cultured in vitro were treated with different concentration of Ang II for different time, and the viability was measured using cell counting kit-8 (CCK-8). After treatment with 1 × 10-6 mol/L Ang II for 24 h, flow cytometry and Western blot were used to measure the cell apoptosis, and Western blot was used to analyze the protein expression of TXNIP, carbohydrate response element-binding protein (ChREBP) and angiotensin II type 1 receptor (AT1R). Real-time PCR was used to detect TXNIP and ChREBP mRNA expression. IF/ICC was used to observe the TXNIP, ChREBP and AT1R expression. The results showed that Ang II reduced cell viability and induced the expression of TXNIP in a dose- and time-dependent manner (P < 0.05, n = 6) compared with the control group. Ang II induced apoptosis and up-regulated the expression of ChREBP and AT1R (P < 0.05, n = 6). AT1R inhibitor, telmisartan (TM), blocked Ang II-induced TXNIP and ChREBP overexpression (P < 0.05, n = 6) and inhibited Ang II-induced apoptosis. Taken together, Ang II increased ChREBP activation through AT1R, which subsequently increased TXNIP expression and promoted cell apoptosis. These findings suggest a therapeutic potential of targeting TXNIP in preventing Ang II-induced INS-1 cell apoptosis in diabetes.

[Adenovirus-mediated overexpression of thioredoxin interaction protein inhibits INS-1 islet ß cell proliferation].

Diabetes can cause a significant increase in the expression of thioredoxin (Trx)-interacting protein (TXNIP), which binds to Trx and inhibits its activity. The present study was aimed to investigate the effect of TXNIP on proliferation of rat INS-1 islet ß cells and the underlying mechanism. TXNIP overexpressing adenovirus vectors (Ad-TXNIP-GFP and Ad-TXNIPc247s-GFP) were constructed and used to infect INS-1 cells. Ad-TXNIPc247s-GFP vector carries a mutant C247S TXNIP gene, and its expression product (TXNIPc247s) cannot attach and inhibit Trx activity. The expression of TXNIP was detected by real-time PCR and Western blot. EdU and Ki67 methods were used to detect cell proliferation. Protein phosphorylation levels of ERK and AKT were detected by Western blot. The results showed that both TXNIP and TXNIPc247s protein overexpressions inhibited the proliferation of INS-1 cells, and the former's inhibitory effect was greater. Moreover, both of the two kinds of overexpressions inhibited the phosphorylation of ERK and AKT. These results suggest that TXNIP overexpression may inhibit the proliferation of INS-1 cells through Trx-dependent and non-Trx-dependent pathways, and the mechanism involves the inhibition of ERK and AKT phosphorylation.

Identification and verification of genes associated with hypoxia microenvironment in Alzheimer's disease.

As the incidence of Alzheimer's disease (AD) increases year by year, more people begin to study this disease. In recent years, many studies on reactive oxygen species (ROS), neuroinflammation, autophagy, and other fields have confirmed that hypoxia is closely related to AD. However, no researchers have used bioinformatics methods to study the relationship between AD and hypoxia. Therefore, our study aimed to screen the role of hypoxia-related genes in AD and clarify their diagnostic significance. A total of 7681 differentially expressed genes (DEGs) were identified in GSE33000 by differential expression analysis and cluster analysis. Weighted gene co-expression network analysis (WGCNA) was used to detect 9 modules and 205 hub genes with high correlation coefficients. Next, machine learning algorithms were applied to 205 hub genes and four key genes were selected. Through the verification of external dataset and quantitative real-time PCR (qRT-PCR), the AD diagnostic model was established by ANTXR2, BDNF and NFKBIA. The bioinformatics analysis results suggest that hypoxia-related genes may increase the risk of AD. However, more in-depth studies are still needed to investigate their association, this article would guide the insights and directions for further research.

Biomass Bottom Ash as Supplementary Cementitious Material: The Effect of Mechanochemical Pre-Treatment and Mineral Carbonation.

The need to mitigate the CO2 emissions deriving from the cement industry becomes imperative as the climate crisis advances. An effective strategy to achieve this is increasing the replacement level of cement clinkers by waste-derived supplementary cementitious materials (SCMs). In this study, the use of mechanochemically activated biomass ash for high-volume (up to 40%) substitution of cement is investigated. The effect of mineral carbonation treatment on the performance of the mechanochemically treated biomass ash as SCM was also examined. The results showed that the mechanochemically treated biomass ash was the most effective SCM, with the respective samples at 40% cement replacement reaching 63% of the strength at 28 days as compared to samples with 100% Portland cement, while only 17% of the strength was achieved in samples with 40% untreated biomass ash. As suggested by the isothermal calorimetry, XRD, FTIR, and TG analysis, the mechanochemical treatment enhanced the reactivity and the filler effect of the biomass ash, leading to improved mechanical performances of these mortars compared to those containing untreated biomass ash. Mineral carbonation reduced the reactivity of the mechanochemically treated biomass ash but still led to better strength performances in comparison to the untreated biomass ash.

Machine learning models identify ferroptosis-related genes as potential diagnostic biomarkers for Alzheimer's disease.

Alzheimer's disease (AD) is a complex, and multifactorial neurodegenerative disease. Previous studies have revealed that oxidative stress, synaptic toxicity, autophagy, and neuroinflammation play crucial roles in the progress of AD, however, its pathogenesis is still unclear. Recent researches have indicated that ferroptosis, an iron-dependent programmed cell death, might be involved in the pathogenesis of AD. Therefore, we aim to screen correlative ferroptosis-related genes (FRGs) in the progress of AD to clarify insights into the diagnostic value. Interestingly, we identified eight FRGs were significantly differentially expressed in AD patients. 10,044 differentially expressed genes (DEGs) were finally identified by differential expression analysis. The following step was investigating the function of DEGs using gene set enrichment analysis (GSEA). Weight gene correlation analysis was performed to explore ten modules and 104 hub genes. Subsequently, based on machine learning algorithms, we constructed diagnostic classifiers to select characteristic genes. Through the multivariable logistic regression analysis, five features (RAF1, NFKBIA, MOV10L1, IQGAP1, FOXO1) were then validated, which composed a diagnostic model of AD. Thus, our findings not only developed genetic diagnostics strategy, but set a direction for further study of the disease pathogenesis and therapy targets.