BACKGROUND: Corticosteroids have been used for refractory Mycoplasma pneumoniae pneumonia and have beneficial effects. The aim of this study was to identify the biomarkers for predicting refractory M. pneumoniae pneumonia in a timely fashion to initiate steroid therapy. METHODS: This was a prospective cohort study of children with M. pneumoniae pneumonia admitted to the Children's Hospital of Fudan University from September 2012 to August 2013. Lactate dehydrogenase (LDH) and other laboratory tests, including complete blood counts, C-reactive protein, erythrocyte sedimentation rate (ESR), alanine aminotransferase, aspartate aminotransferase, ␣-hydroxybutyrate dehydrogenase (HBDH), creatine kinase, and creatine kinase MB, were performed on admission. Based on the definition of refractory M. pneumoniae pneumonia, subjects were divided into 2 groups: refractory M. pneumoniae pneumonia and usual M. pneumoniae pneumonia.The diagnostic values of laboratory findings were analyzed. RESULTS: In total, 653 subjects were enrolled, including 300 in the refractory pneumonia group and 353 in the usual pneumonia group. There was no significant difference in sex distribution between the 2 groups. The average age in the refractory M. pneumoniae pneumonia group was greater than that in the usual M. pneumoniae pneumonia group. Compared with the usual pneumonia group, the refractory pneumonia group showed significantly higher levels of C-reactive protein, serum LDH, serum HBDH, serum alanine aminotransferase, serum aspartate aminotransferase, and neutrophils and higher ESRs. Logistic regression showed that age, LDH, and ESR were the significant factors in predicting refractory M. pneumoniae pneumonia. In addition, LDH and HBDH were strongly correlated, and receiver operating characteristic curve analysis showed that the area under the curve of LDH was 0.718 with a cutoff of 379 IU/L, that of ESR was 0.683 with a cutoff of 32.5 IU/L, and that of HBDH was 0.691 with a cutoff of 259.5 IU/L. CONCLUSIONS: Serum LDH can be used as a biomarker to predict refractory M. pneumoniae pneumonia at the early stage of hospitalization.

We aimed to explore the mechanism of pramipexole (PPX) actions in the treatment of Parkinson’s disease (PD). Genes related to PD and PPX were screened through bioinformatics retrieval. The PD model was constructed by applying 1-methyl-4-phenylpyridinium (MMP+). The RNA expression levels of circSNCA, SNCA, apoptosis-related genes (BCL2, CASP3, BAX, PTEN and P53) and miR-7 were detected by qRT-PCR. Protein expression was determined by western blot. The interactions between circSNCA-miR-7-SNCA were verified by dual luciferase assay and immunofluorescence localization. Cell viability was determined by MTT assay. SNCA and circSNCA expression levels in PD were downregulated after PPX treatment, consistent with the levels of pro-apoptotic genes. CircSNCA increased SNCA expression by downregulating miR-7 in PD as a competitive endogenous RNA (ceRNA). Lower circSNCA expression was associated with the reduced expression of pro-apoptotic (CASP3, BAX, PTEN and P53) proteins. CircSNCA downregulation could decrease apoptosis and induce autophagy in PD. In conclusion, the downregulation of circSNCA by PPX treatment reduced cell apoptosis and promoted cell autophagy in PD via a mechanism that served as a miR-7 sponge to upregulate SNCA.

Cancer is a multifaceted disease that results from dysregulated normal cellular signaling networks caused by genetic, genomic and epigenetic alterations at cell or tissue levels. Uncovering the underlying protein signaling network changes, including cell cycle gene networks in cancer, aids in understanding the molecular mechanism of carcinogenesis and identifies the characteristic signaling network signatures unique for different cancers and specific cancer subtypes. The identified signatures can be used for cancer diagnosis, prognosis, and personalized treatment. During the past several decades, the available technology to study signaling networks has significantly evolved to include such platforms as genomic microarray (expression array, SNP array, CGH array, etc.) and proteomic analysis, which globally assesses genetic, epigenetic, and proteomic alterations in cancer. In this review, we compared Pathway Array analysis with other proteomic approaches in analyzing protein network involved in cancer and its utility serving as cancer biomarkers in diagnosis, prognosis and therapeutic target identification. With the advent of bioinformatics, constructing high complexity signaling networks is possible. As the use of signaling network-based cancer diagnosis, prognosis and treatment is anticipated in the near future, medical and scientific communities should be prepared to apply these techniques to further enhance personalized medicine.

Combined treatment of ciprofloxacin and glucocorticoids can significantly ameliorate child refractory M. pneumoniae pneumonia further comparative study is needed to well evaluate the treatment efficacy.