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Riemerella anatipestifer is a Gram-negative bacterium that can cause disease in a wide range of wild and domesticated birds, especially waterfowl. The presence of an antibiotic-resistance gene in R. anatipestifer has not yet been reported, indicating the need for investigation. In the present study, 40.5% of R. anatipestifer isolates were found to exhibit resistance to chloramphenicol, while 45.9% showed intermediate resistance and 13.5% were susceptible to chloramphenicol, an antibiotic that has been prohibited for use in food animals in Taiwan since 2003. The resistance gene was identified as the cat gene and cloned by library sequencing. The prevalence of the cat gene in Taiwanese R. anatipestifer isolates was 78.4%. The position of the cat gene was then determined within the novel plasmid, designated pRA0511. pRA0511 was sequenced and shown to be 11,435 bp in size with 10 open reading frames (ORFs). Proteins putatively encoded by these 10 ORFs included four drug-resistance-associated proteins. Two proteins designed as chloramphenicol acetyltransferases (CATs) were encoded by two non-adjacent ORFs, and the other two were TetX2 and a multi-drug ABC transporter permease/ATPase. The putative CAT protein had 62.9 to 79.5% homology to a known type B CAT. The pRA0511 plasmid is the first identified drug-resistance plasmid in R. anatipestifer, more specifically associated with chloramphenicol resistance.

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Abstract. This paper presents a neuro-fuzzy classifer for activity recognition using one triaxial accelerometer and feature reduction approaches. We use a triaxial accelerometer to acquire subjects' acceleration data and train the neurofuzzy classifier to distinguish different activities/movements. To construct the neuro-fuzzy classifier, a modified mapping-constrained agglomerative clustering algorithm is devised to reveal a compact data configuration from the acceleration data. In addition, we investigate two different feature reduction methods, a feature subset selection and linear discriminate analysis. These two methods are used to determine the significant feature subsets and retain the characteristics of the data distribution in the feature space for training the neuro-fuzzy classifier. Experimental results have successfully validated the effectiveness of the proposed classifier.

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A septicemic outbreak in southern Taiwan duck farms in 2014 resulted in high mortality of ducklings. Samples from oral or cloacal sites of a®ected Muscovy and Pekin ducks were collected and the identity of the¯eld isolates was con¯rmed using Riemerella anatipestifer (RA) 16S rRNA and outer membrane protein A (OmpA)-speci¯c primers in polymerase chain reactions (PCR), with 15 isolates found positive for both 16S rRNA and OmpA. Detection of both the 16S rRNA and OmpA genes could be a rapid PCR test for RA. Serotyping of the isolates using gel-di®usion precipitin test identi¯ed serotypes 1, 4, 6, 17, and 19 while a number of isolates were unidenti¯able. Sequence analysis of the OmpA gene found high identity (99.0-99.7%) among isolates in Taiwan. These results indicate that RA remains as a signi¯cant cause of duck septicemic disease in southern Taiwan.