Identification of microRNAs for the early diagnosis of Parkinson's disease and multiple system atrophy.

MicroRNAs are reportedly involved in the pathogenesis of neurodegenerative diseases, including Parkinson's disease and multiple system atrophy. We previously identified 7 differentially expressed microRNAs in Parkinson's disease patients and control sera (miR-30c, miR-31, miR-141, miR-146b-5p, miR-181c, miR-214, and miR-193a-3p). To investigate the expression levels of the 7 serum microRNAs in Parkinson's disease and multiple system atrophy, 23 early Parkinson's disease patients (who did not take any anti- Parkinson's disease drugs), 23 multiple system atrophy patients, and 24 normal controls were recruited at outpatient visits in this study. The expression levels of the 7 microRNAs in serum were detected using quantitative real-time polymerase chain reaction. A receiver operating characteristic curve was used to evaluate whether microRNAs can differentially diagnose Parkinson's disease and multiple system atrophy. Clinical scales were used to analyze the correlations between serum microRNAs and clinical features. The results indicated that miR-214 could distinguish Parkinson's disease from the controls, and another 3 microRNAs could differentiate multiple system atrophy from the controls (miR-141, miR-193a-3p, and miR-30c). The expression of miR-31, miR-141, miR-181c, miR-193a-3p, and miR-214 were lower in multiple system atrophy than in Parkinson's disease (all P < 0.05). Combinations of microRNAs accurately discriminated Parkinson's disease from multiple system atrophy (area under the receiver operating characteristic curve = 0.951). For the correlation analysis, negative correlations were discovered between the expression of miR-214 and the Hamilton Anxiety Scale and Parkinson's Disease Non-Motor Symptom scores (all P < 0.05). Our results demonstrate that the distinctive characteristics of microRNAs differentiate Parkinson's disease and multiple system atrophy patients from healthy controls and may be used for the early diagnosis of Parkinson's disease and multiple system atrophy.

Prenatal diagnosis for a Chinese family with a de novo DMD gene mutation: A case report.

BACKGROUND: Patients with Duchenne muscular dystrophy (DMD) usually have severe and fatal symptoms. At present, there is no effective treatment for DMD, thus it is very important to avoid the birth of children with DMD by effective prenatal diagnosis. We identified a de novo DMD gene mutation in a Chinese family, and make a prenatal diagnosis. METHODS: First, multiplex ligation-dependent probe amplification (MLPA) was applied to analyze DMD gene exon deletion/duplication in all family members. The coding sequences of 79 exons in DMD gene were analyzed by Sanger sequencing in the patient; and then according to DMD gene exon mutation in the patient, DMD gene sequencing was performed in the family members. On the basis of results above, the pathogenic mutation in DMD gene was identified. RESULTS: MLPA showed no DMD gene exon deletion/duplication in all family members. Sanger sequencing revealed c.2767_2767delT [p.Ser923LeufsX26] mutation in DMD gene of the patient. Heterozygous deletion mutation (T/-) at this locus was observed in the pregnant woman and her mother and younger sister. The analyses of amniotic fluid samples indicated negative Y chromosome sex-determining gene, no DMD gene exon deletion/duplication, no mutations at c.2767 locus, and the inherited maternal X chromosome different from that of the patient. CONCLUSION: The pathogenic mutation in DMD gene, c.2767_2767delT [p.Ser923LeufsX26], identified in this family is a de novo mutation. On the basis of specific conditions, it is necessary to select suitable methods to make prenatal diagnosis more effective, accurate, and economic.

Identification of the microbial community composition and structure of coal-mine wastewater treatment plants.

The wastewater from coal-mine industry varies greatly and is resistant to biodegradation for containing large quantities of inorganic and organic pollutants. Microorganisms in activated sludge are responsible for the pollutants' removal, whereas the microbial community composition and structure are far from understood. In the present study, the sludges from five coal-mine wastewater treatment plants were collected and the microbial communities were analyzed by Illumina high-throughput sequencing. The diversities of these sludges were lower than that of the municipal wastewater treatment systems. The most abundant phylum was Proteobacteria ranging from 63.64% to 96.10%, followed by Bacteroidetes (7.26%), Firmicutes (5.12%), Nitrospira (2.02%), Acidobacteria (1.31%), Actinobacteria (1.30%) and Planctomycetes (0.95%). At genus level, Thiobacillus and Comamonas were the two primary genera in all sludges, other major genera included Azoarcus, Thauera, Pseudomonas, Ohtaekwangia, Nitrosomonas and Nitrospira. Most of these core genera were closely related with aromatic hydrocarbon degradation and denitrification processes. Identification of the microbial communities in coal-mine wastewater treatment plants will be helpful for wastewater management and control.