No abstract

Since brain tissue is not readily accessible, a new focus in search of biomarkers for schizophrenia is blood-based expression profiling of non-protein coding genes such as microRNAs (miRNAs), which regulate gene expression by inhibiting the translation of messenger RNAs. This study aimed to identify potential miRNA signature for schizophrenia by comparing genome-wide miRNA expression profiles in patients with schizophrenia vs. healthy controls. A genome-wide miRNA expression profiling was performed using a Taqman array of 365 human miRNAs in the mononuclear leukocytes of a learning set of 30 cases and 30 controls. The discriminating performance of potential biomarkers was validated in an independent testing set of 60 cases and 30 controls. The expression levels of the miRNA signature were then evaluated for their correlation with the patients' clinical symptoms, neurocognitive performances, and neurophysiological functions. A seven-miRNA signature (hsa-miR-34a, miR-449a, miR-564, miR-432, miR-548d, miR-572 and miR-652) was derived from a supervised classification with internal cross-validation, with an area under the curve (AUC) of receiver operating characteristics of 93%. The putative signature was then validated in the testing set, with an AUC of 85%. Among these miRNAs, miR-34a was differentially expressed between cases and controls in both the learning (P = 0.005) and the testing set (P = 0.002). These miRNAs were differentially correlated with patients' negative symptoms, neurocognitive performance scores, and event-related potentials. The results indicated that the mononuclear leukocyte-based miRNA profiling is a feasible way to identify biomarkers for schizophrenia, and the seven-miRNA signature warrants further investigation.

To group infectious bronchitis virus (IBV) isolates, a genetic grouping method based on hypervariable region 1 (HVR 1, nucleotides 168 to 197) was compared with that based on the whole S1 gene. Both methods resulted in the same grouping data. So the grouping method based on HVR 1 could represent the grouping method based on the whole S1 gene. Taiwan isolates could not be placed within the existing groups. In order to test the correlation between genotype and serotype, a one-way neutralization test was used to compare 9 Taiwan isolates selected from different genotypes with Massachusetts (Mass) (H120) and Connecticut (Conn) standard strains. In addition, a two-way cross-neutralization test was performed in embryonated eggs with the beta method (constant-virus, diluted-serum) and the reciprocal neutralization titers were calculated to give the relatedness (r) values. The results of two kinds of neutralizing tests showed that the serotypes of 9 isolates were different from Mass or Conn. Based on the r-values, 9 isolates were divided into two serotypes which were correlated with their genotypes. From pathogenicity tests, IBV Taiwan isolates could be divided into high, intermediate, and low pathogenicity according to their pathogenicity indexes. However, no relationship exists between pathotype and genotype. In conclusion, the genetic typing method based on HVR 1 can be used for typing IBV isolates.

No abstract

Adenovirus type 7 caused a high proportion of severe infections.