Big Data Technology in the Macrodecision-Making Model of Regional Industrial Economic Information Applied Research.

In the era of Internet +, modern industry has developed rapidly, the network economy has promoted the great development of the industrial economy, and the traditional industrial economic statistics method has not been suitable for the development needs of modern enterprises. In today's society, it can be described as the era of big data, the use of big data technology for industrial economic statistics is needed for the development of industrial modernization, and it is also a new requirement for industrial economic statistics put forward by social development. With the wide application of Internet of Things, cloud computing, mobile Internet, remote sensing, and geographic information technology in the economic field, precise economic policies have gradually developed and matured. Especially for different industries in the regional economy, according to the big data in the region, the big data mining technology and analysis technology can be used to obtain the development situation and future trend of the industrial economy in a timely and effective manner. Applying big data technology to macrodecision of regional economic information is an effective way to make macrodecision of current economy. Based on this background, this paper proposes a macroeconomic decision-making method for regional industries based on big data technology. Using data mining technology, time series data analysis methods combined with artificial intelligence analysis, the development trend of regional industries is obtained, and then the development trend of the industry is obtained. Development makes macroeconomic decisions. Taking agriculture as an example, the most popular analysis of the price trend of a certain agricultural product provides an effective reference for the development strategy of this agricultural product. The results show that the method proposed in this paper can effectively apply big data technology to the macrodecision-making of regional industrial economy. And it has better promotion significance.

Erratum to microRNA-188 aggravates contrast-induced apoptosis by targeting SRSF7 in novel isotonic contrast-induced acute kidney injury rat models and renal tubular epithelial cells.

[This corrects the article DOI: 10.21037/atm.2019.07.20.].

MicroRNA-188 aggravates contrast-induced apoptosis by targeting SRSF7 in novel isotonic contrast-induced acute kidney injury rat models and renal tubular epithelial cells.

BACKGROUND: Contrast media (CM) is widely used in cardiac catheterization; however, it may cause contrast-induced acute kidney injury (CI-AKI) which severely increases mortality. MicroRNA (miRNA) has been found to participate in the process of acute kidney injury (AKI), and this discovery has great potential for diagnosis and treatment. However, the role of miRNA in CI-AKI is still unclear. This study aimed to investigate the regulatory effect miRNAs exert in CI-AKI. METHODS: We established a novel, representative, isotonic CI-AKI model by using CM iodixanol, a CM which is commonly used in clinic. Next-generation sequencing and reverse transcription polymerase chain reaction (RT-qPCR) were performed to determine the expression of miRNA-188 in CI-AKI. Western blot analysis of the apoptosis regulator protein and TUNEL assay were ordered to evaluate apoptosis. Bioinformatics and double luciferin reporter gene assay were performed to predict and to confirm the interaction between microRNA-188 and SRSF7. RESULTS: The novel isotonic CI-AKI rat model we established exhibited typical characteristics of CI-AKI in serum creatinine, cystatin C, HE staining, and under electron microscope observation. Sequencing and RT-qPCR demonstrated that miRNA-188 was significantly up-regulated both in CI-AKI rat and HK-2 cell models while overexpression of miRNA-188 significantly aggravated apoptosis in CI-AKI cell models. SRSF7 was identified as a direct target gene of miRNA-188, and dual luciferase reporter assay determined the direct interaction between SRSF7 and miRNA-188. In addition, SRSF7 silencing reduced the cell viability rate of the CI-AKI cell model. CONCLUSIONS: The present study's findings indicate that miRNA-188 aggravated contrast-induced apoptosis by regulating SRSF7, which may serve as a potential drug target for CI-AKI intervention.

Correction: Predictive value of post-procedural early (within 24 h) increase in cystatin C for contrast-induced acute kidney injury and mortality following coronary angiography or intervention.

[This corrects the article DOI: 10.18632/oncotarget.19034.].

Predictive value of post-procedural early (within 24 h) increase in cystatin C for contrast-induced acute kidney injury and mortality following coronary angiography or intervention.

OBJECTIVE: To investigate the predictive value of post-procedural early (within 24 h) increase in cystatin C for contrast-induced acute kidney injury (CI-AKI) and all-cause mortality following coronary angiography or intervention. METHODS: We prospectively investigated 1042 consecutive patients with both baseline and early post-procedural cystatin C measurement undergoing coronary angiography or intervention. CI-AKI was defined as an increase ≥0.3 mg/dL or >50% in serum creatinine from baseline within 48 h post-procedure. Mean follow-up was 2.26 years. RESULTS: Overall, the patients had a CI-AKI incidence was 3.6% (38/1042), mean serum creatinine of 87 µmol/L. Compared with Mehran risk score, post-procedural early absolute increase (AUC: 0.584 vs. 0.706, P = 0.060) and relative increase (AUC: 0.585 vs. 0.706, P = 0.058) in cystatin C had poorer predictive value for CI-AKI. According to multivariate analysis, post-procedural significant early increase (≥0.3 mg/dL or ≥10%) in cystatin C developed in 231 patients (22.2%), was not independent predictor of CI-AKI (adjusted OR: 1.23, 95% CI, 0.56-2.69, P = 0.612), and long-term mortality (adjusted HR: 0.90; P = 0.838). CONCLUSIONS: Our data suggested post-procedural early increase (within 24 h) in cystatin C was not effective for predicting CI-AKI or all-cause mortality following coronary angiography or intervention among patients at relative low risk of CI-AKI, the negative finding of poor predictive value should be further evaluated in larger multicenter trials.