Identification and Characterization of MicroRNAs in Normal Equine Tissues by Next Generation Sequencing

The role of microRNAs (miRNAs) as a post-transcriptional gene regulator has been elucidated in a broad range of organisms including domestic animals. Characterization of miRNAs in normal tissues is an important step to investigate the functions of miRNAs in various physiological and pathological conditions. Using Illumina Next Generation Sequencing (NGS) technology, we identified a total of 292 known and 329 novel miRNAs in normal horse tissues including skeletal muscle, colon and liver. Distinct sets of miRNAs were differentially expressed in a tissue-specific manner. The miRNA genes were distributed across all the chromosomes except chromosomes 29 and 31 in the horse reference genome. In some chromosomes, multiple miRNAs were clustered and considered to be polycistronic transcript. A base composition analysis showed that equine miRNAs had a higher frequency of A+U than G+C. Furthermore, U tended to be more frequent at the 59 end of miRNA sequences. This is the first experimental study that identifies and characterizes the global miRNA expression profile in normal horse tissues. The present study enriches the horse miRNA database and provides useful information for further research dissecting biological functions of miRNAs in horse.open2

Packages of Care for Depression in Low- and Middle-Income Countries

In the first in a series of six articles on packages of care for mental disorders in low- and middle-income countries, Neerja Chowdary and colleagues discuss the treatment of depression

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified