Background/Aims: Ischemic heart disease is a leading cause of death in cardiovascular diseases, and microRNAs (miRs) have been reported to be potential therapeutic targets in heart disease. Herein, this study aims to investigate the effects of microRNA (miR)-374 on myocardial ischemia-reperfusion (I/R) injury in rat models pretreated with sevoflurane by targeting SP1 through the PI3K/Akt pathway. Methods: SD rats were grouped into sham, I/R and sevoflurane + I/R (sevoflurane preconditioning and I/R) groups. The biochemical indicators, pathological changes, positive expression of SP1 protein, and apoptosis rates were measured using biochemical detection, Evans blue-TTC staining, immunohistochemistry and TUNEL staining. RT-qPCR and Western blotting were used to investigate the expression of miR-374 mRNA and the protein expression of SP1, PI3K, HO-1, p53, iNOS, c-fos, Akt/p-Akt, and GSK-3β/p-GSK-3β. Cardiomyocytes were treated with miR-374 mimics, miR-374 inhibitors, or siRNA-SP1. Cardiomyocyte proliferation and cycle distribution and apoptosis were studied by MTT and flow cytometry. Results: Compared with the I/R group, in the sevoflurane + I/R group, serum SOD and IL-10 increased, while MDA, LDH, CK, TNF-α, IL-6 and IL-10 decreased, as did the percentage of infarct area, the positive rate of SP1 and the apoptosis index. The expression of SP1, p53, iNOS and c-fos decreased, and the miR-374 expression of PI3K, HO-1, Akt/p-Akt, GSK-3β/p-GSK-3β increased. With the upregulation of miR-374 and the downregulation of SP1, the expression of SP1, p53, iNOS and c-fos decreased, as did the proportion of cells in G1 phase and the apoptosis rate; the expression of PI3K, HO-1, Akt/p-Akt, GSK-3β/p-GSK-3β increased. The results in the miR-374 inhibitor group contrasted with the above results. Conclusion: The results indicated that miR-374 could alleviate myocardial I/R damage in rat models pretreated with sevoflurane by targeting SP1 by activating the PI3K/Akt pathway.
MicroRNAs (miRNAs) are important regulators that play key roles in tumorigenesis and tumor progression. In this study, we investigate whether let-7b acts as a tumor suppressor to inhibit invasion and metastasis in gastric cancers. We analyzed the expression of let-7b in 60 pair-matched gastric neoplastic and adjacent non-neoplastic tissues by quantitative real-time polymerase chain reaction. Functional analysis of let-7b expression was assessed in vitro in gastric cancer cell lines with let-7b precursor and inhibitor. The roles of let-7b in tumorigenesis and tumor metastasis were analyzed using a stable let-7b expression plasmid in nude mice. A luciferase reporter assay was used to assess the effect of let-7b on inhibitor of growth family, member 1 (ING1) expression. Real-time PCR showed decreased levels of let-7b expression in metastatic gastric cancer tissues and cell lines that are potentially highly metastatic. Cell invasion and migration were significantly impaired in GC9811-P and SGC7901-M cell lines after transfection with let-7b mimics. Nude mice with xenograft models of gastric cancer confirmed that let-7b could inhibit gastric cancer metastasis in vivo after transfection by the lentivirus pGCsil-GFP- let-7b. Luciferase reporter assays demonstrated that let-7b directly binds to the 3'-UTR of ING1, and real-time PCR and western blotting further indicated that let-7b downregulated the expression of ING1 at the mRNA and protein levels. Our study demonstrates that overexpression of let-7b in gastric cancer can inhibit invasion and migration of gastric cancer cells through directly targeting the tumor metastasis-associated gene ING1. These findings help clarify the molecular mechanisms involved in gastric cancer metastasis and indicate that let-7b modulation may be a bona fide treatment of gastric cancer.
The study aims to explore the effects of microRNA-206 (miR-206) targeting IGF-1 on the activation of hippocampal astrocytes in aged rats induced by sevoflurane through the PI3K/AKT/CREB signaling pathway. Wistar rats and astrocytes were divided into the normal/blank, sham/negative control (NC), sevoflurane (sevo), miR-206 mimics+sevo, miR-206 inhibitors+sevo, miR-206 NC+sevo, IGF-1 shRNA+sevo, and miR-206 inhibitors+IGF-1 shRNA+sevo groups. The Morris water maze test was exhibited to assess the cognitive functions. Glial fibrillary acidic protein (GFAP) expression was detected by immunofluorescence assay. Western blotting and RT-qPCR were used to detect the expression of miR-206, IGF-1, PI3K, AKT, CREB, pPI3K, pAKT, pCREB, cytochrome-c (Cyt-c), and caspase-3. Cell viability and apoptosis were detected by MTT assay and annexin V/PI double staining respectively. Mitochondrial transmembrane potential (MTP) were determined by flow cytometry. The IGF-1 shRNA+sevo group showed reduced miR-206 expression. Compared with the normal/blank group, the sevo, and miR-206 NC+sevo groups showed decreased miR-206 and GFAP expressions, cell viability and MTP but increased expressions of IGF-1, PI3K, AKT, CREB, pPI3K, pAKT, pCREB, Cyt-c and caspase-3, as well as cell apoptosis. Similar trends were observed in the miR-206 inhibitors+sevo group when compared with the sevo group. The study provides evidence that miR-206 alleviates the inhibition of activation of hippocampal astrocytes in aged rats induced by sevoflurane by targeting IGT-1 through suppressing the PI3K/AKT/CREB signaling pathway.
Background/Aims: Long non-coding RNA (lncRNA) and glucagon-like peptide 1 receptor (GLP-1R) are crucial for heart development and for adult heart structural maintenance and function. Herein, we performed a study to explore the effect of lncRNA LINC00652 (LINC00652) on myocardial ischemia-reperfusion (I/R) injury by targeting GLP-1R through the cyclic adenosine monophosphate-protein kinase A (cAMP/PKA) pathway. Methods: Bioinformatics software was used to screen the long-chain non-coding RNAs associated with myocardial ischemia-reperfusion and to predict target genes. The mRNA and protein levels of LINC00652, GLP-1R and CREB were detected by RT-qPCR and western blotting. In order to identify the interaction between LINC00652 and myocardial I/R injury, the cardiac function, the hemodynamic changes, the pathological changes of the myocardial tissues, the myocardial infarct size, and the apoptosis of myocardial cells of mice were measured. Meanwhile, the levels of serum IL-1β and TNF-α were detected. Results: LINC00652 was overexpressed in the myocardial cells of mice with myocardial I/R injury. GLP-1R is the target gene of LINC00652. We also determined higher levels of LINC00652 and GLP-1R in the I/R modeled mice. Additionally, si-LINC00652 decreased cardiac pathology, infarct size, apoptosis rates of myocardial cells, and levels of IL-1β and TNF-α, and increased GLP-1R expression cardiac function, normal hemodynamic index, and the expression and phosphorylation of GLP-1R and CREB proteins. Conclusion: Taken together, our key findings of the present highlight LINC00652 inhibits the activation of the cAMP/PKA pathway by targeting GLP-1R to reduce the protective effect of sevoflurane on myocardial I/R injury in mice.
Background: Compared with lobectomy, the anatomical structure of the lung segment is relatively complex and easy to occur variation, thus it increases the difficulty and risk of precise segmentectomy. The application of three-dimensional computed tomography bronchography and angiography (3D-CTBA) combined with a three-dimensional printing (3D printing) model can ensure the safety of operation and simplify the surgical procedure to a certain extent. We aimed to estimate the value of 3D-CTBA and 3D printing in thoracoscopic precise pulmonary segmentectomy. Methods: We retrospectively reviewed the clinical data of 65 patients who underwent anatomical segmentectomy at the Affiliated Hospital of Shaoxing University from January 2019 to August 2020. The patients were divided into two groups: a 3D-CTBA combined with 3D printing group (30 patients) and a general group (35 patients). The perioperative data of the two groups were compared. Results: Compared with the general segmentectomy group at the same period in our center, the surgery time of the group guided by 3D-CTBA and 3D printing was significantly shorter. Intraoperative blood loss in the 3D-CTBA and 3D printing group was also apparently lower than in the general group. Hospital stay and postoperative chest tube duration showed no significant differences between the two groups, and neither did postoperative complications such as pneumonia, hemoptysis, arrhythmia, and pulmonary air leakage.Conclusions: 3D-CTBA combined with 3D printing clearly identifies the precise pulmonary segmental structures, avoids intraoperative accidental injury, reduces intraoperative blood loss, shortens the operation time and improves the safety of thoracoscopic pulmonary segmentectomy in stage IA non-small cell lung cancer (NSCLC).
Two new flavonoids, corylifol F (1) and corylifol G (2), together with 19 known compounds, were isolated from the fruits of Psoralea corylifolia L.. The structures of these compounds were determined by interpretation of spectroscopic data and comparison with literature properties. The radioprotective effects of the isolated compounds against ionising radiation damage were also evaluated in vitro. The results showed that corylifol A exhibited radioprotective effects in both HBL-100 and MCF-7 cells, while psoralen, isopsoralen, corylifol C and bakuchiol showed obvious selective action to protect HBL-100 cells against damage caused by ionising radiation.
To explore the application of neural network algorithm model in lung cancer imaging, and provide reference for the application and development of artificial neural network (ANN) algorithm model in lung cancer medical mirroring, so as to promote the development of ANN in this field. Meanwhile, it is hoped that the application of neural network algorithms in medical imaging can improve the survival rate and cure rate of lung cancer. In this study, an ANN algorithm model was selected to establish a lung cancer recognition model. After determining the lung cancer lesion area, the image segmentation algorithm was used to separately display the lung cancer lesion area, and a comparison experiment was designed to verify the accuracy of the model. ANNs were used to identify lung cancer, which can be concluded that the accuracy is 94.6%, the sensitivity is 95.7%, and the specificity is 93.5%. By combining image retrieval methods with lung cancer image segmentation algorithms, the lesion area of lung cancer can be clearly displayed. Therefore, the lung cancer image segmentation algorithm based on the neural network model has good recognition performance. This research can provide reference for the application of neural network algorithm model in the field of cancer diagnosis and treatment.
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