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Aim: Common indoor pollutants, as fine particulate matter (PM2.5), can damage people's health and cause skin allergies. However, it remains unknown which common pollutants can lead to allergy, such as, in children atopic dermatitis, and what is the key molecule. This study aimed to investigate the thymic stromal lymphopoietin (TSLP) produced from keratinocytes after environmental pollutant stimulation. Methods: PAM212 cells were treated by several pollutants, including PM2.5, formaldehyde, m-xylene, and 1,2,4-trimethylbenzene, and tried to analyze their relationships. The mRNA expression level of TSLP was determined by qPCR. The protein level of TSLP was detected by ELISA analysis. Results: The mRNA expression of TSLP was significantly up-regulated when PAM212 cells were stimulated by PM2.5 at 25 μg/ml for 12 h. Meanwhile, the protein level of TSLP in culture supernatant was increased. However, TSLP protein production was not detected in culture supernatant treated with formaldehyde, m-xylene, and 1, 2, 4-trimethylbenzene. Conclusion: PM2.5 promotes the expression of TSLP and may aggravate allergic response using this pathway. [ABSTRACT FROM AUTHOR]

High mobility group AT-hook 1 (HMGA1) is able to regulate gene expression and function as a tumour suppressor. The spatiotemporal expression pattern of HMGA1 was investigated in this study. Immature female rats (22–23 days old) were treated with 10 IU, s.c., pregnant mare's serum gonadotrophin to stimulate follicular development, followed 48 h later by injection with 5 IU, s.c., human chorionic gonadotrophin (hCG). Whole ovaries or granulosa cells were collected at various times after hCG administration (n = 3 per time point). Real-time polymerase chain reaction and western blot analysis revealed that HMGA1 was highly stimulated in the ovary by 4–12 h after hCG treatment. In situ hybridisation analysis demonstrated that Hmga1 mRNA expression was induced in granulosa cells between 8 and 12 h after hCG treatment. There was negligible Hmga1 mRNA signal observed in newly forming corpora lutea. In addition, the data indicated that both the protein kinase (PK) A and PKC pathways regulated Hmga1 expression in rat granulosa cells. In rat granulosa cell cultures, upregulation of Hmga1 was dependent on new protein synthesis because Hmga1 was inhibited by cycloheximide. Furthermore, Hmga1 mRNA expression in rat granulosa cell cultures was inhibited by AG1478, whereas NS398 and RU486 had no effect, suggesting that Hmga1 expression was regulated, in part, by the epidermal growth factor pathway. In summary, the findings of this study suggest that induction of Hmga1 may be important for theca and granulosa cell differentiation into luteal cells. Transcription factors are essential mediators of ovulation and luteinisation. The present study demonstrates that there are significantly increase in levels of the transcription factor high mobility group AT-hook 1 (HMGA1) after administration of human chorionic gonadotropin to rats. Induction of Hmga1 mRNA is mediated through both the protein kinase (PK) A and PKC signalling pathways by activation of the epidermal growth factor receptor and requires the synthesis of a new protein(s). Temporal stimulation of HMGA1 may be important for theca and granulosa cell differentiation into luteal cells. [ABSTRACT FROM AUTHOR]

Myocardial fibrosis (MF) can cause heart remodeling and it is an independent risk factor for malignant arrhythmias, sudden cardiac death, and other malignant cardiovascular events. It is often characterized by myocardial interstitial collagen deposition and hyperproliferation of cardiac fibroblasts (CFs). The transforming growth factor-β1 (TGF-β1) is the most influential profibrogenic factor. Resveratrol (RSV) is an active polyphenol substance that inhibits myocardial fibrosis. The mechanism of RSV-mediated inhibition of the proliferation of CFs at the microRNA level is not fully understood. We used TGF-β1 to induce CFs proliferation to simulate the pathogenesis of myocardial fibrosis. Neonatal rat CFs were treated with TGF-β1 in the presence or absence of resveratrol. Cell proliferation was measured using the CCK-8 and EdU assay. Collagen secretion was measured using hydroxyproline kit. Further, qPCR analysis was performed to determine microRNA levels after TGF-β1 or resveratrol treatment. To identify the target gene for miR-17, miR-17 was overexpressed or silenced, and the mRNA and protein levels of Smad7 were assessed. The effects of miR-17 silencing or Smad7 overexpression on cell proliferation and collagen secretion were also examined. Resveratrol treatment significantly decreased the TGF-β1-induced CF proliferation and collagen secretion. Resveratrol also decreased the levels of miR-17, miR-34a, and miR-181a in TGF-β1-treated CFs. Overexpression of miR-17 decreased the Smad7 mRNA and protein levels while silencing miR-17 increased them. Additionally, silencing miR-17 or overexpressing Smad7 decreased the TGF-β1-induced CFs proliferation and collagen secretion. In conclusion, resveratrol inhibits TGF-β1-induced CFs proliferation and collagen secretion. This inhibitory effect of resveratrol is orchestrated by the downregulation of miR-17 and the regulation of Smad7. [ABSTRACT FROM AUTHOR]

Background: Since miRNAs can play important roles in different cancer types, how to discover cancer related miRNAs is an important issue. In general, the miRNAs with differential expression is the focus of attention. However, some important cancer related miRNAs are not excavated by differential expression analysis. We take this type of miRNAs as 'dark matters' (DM-miRNA). It is our great interests to develop an algorithm to discover DM-miRNAs. Results: An effective method was developed to find DM-miRNAs. This method is mainly for mining potential DM-miRNAs by building basic miRNA-mRNA network (BMMN) and miRNA-lncRNA network (BMLN). The results indicate that miRNA-mRNA and miRNA-lncRNA interactions can be used as novel cancer biomarkers. Conclusions: The BMMN and BMLN can excavate the non-differentially expressed miRNAs which play an important role in the cancer. What's more, the edge biomarkers (miRNA-mRNA and miRNA-lncRNA interactions) contain more information than the node biomarkers. It will contribute to developing novel therapeutic candidates in cancers. [ABSTRACT FROM AUTHOR]