Tembusu virus (TMUV) associated disease is a growing cause of egg production decrease and encephalitis in domestic waterfowl, with expanding distribution. In previous studies, TMUV isolates were phylogenetically classified into two genetic lineages and different clusters with varied pathogenicity. However, little is known about the phenotypic and virulence characteristics of cluster 3 isolates within the duck TMUV lineage. In this study, the etiological agent causing egg drop in a laying chicken farm in southern China was investigated and a TMUV was isolated from pooled tissue samples.Genome sequencing and phylogenetic analysis grouped the isolate into TMUV cluster 3 with closest relation to the mosquito-origin TMUV YN12193. Cross-neutralization testing using convalescent sera revealed significant antigenic variation between the isolate and a representative strain of cluster 2.2. The experimental infection of SPF hens confirmed the ability of the isolate to replicate in multiple tissues and led to ovary damage. Additionally, high seroconversion rates (95.83%-100%) were detected in the three flocks following retrospective investigation. Our study demonstrates the occurrence of cluster 3 TMUV infection in laying chickens and that the virus exhibits significant antigenic variation compared with cluster 2 TMUV.

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Lumen segmentation in intravascular optical coherence tomography (IVOCT) images is a fundamental work for more advanced plaque analysis, stent recognition, fractional flow reserve (FFR) assessment, and so on. However, the catheter, guide-wire, inadequate blood clearance, and other factors will impact on the accuracy of lumen segmentation. We present a simple and effective method for automatic lumen segmentation method in IVOCT based on morphological features. We use image enhancement, median filtering, image binarization, and morphological closing operation to reduce speckle noise, minimize the effect of blood artifacts and fill in small holes inside vascular walls. We extract the orientation and area-size of connected regions as morphological features in images and remove the catheter and guidewire completely by morphological corrosion operation, small area-size region removal, and orientation morphological feature comparison, and then the contour of the lumen can be discriminated. The evaluation metrics of this method, the Dice index, Hausdorff distance, Jaccard index, and accuracy of 99.32%, 0.06 mm, 99.4%, and 99.66%, respectively, are obtained from comparing with expert annotations on 268 IVOCT images. Compared with the other morphology-based lumen segmentation methods, the presented method can remove the catheter and guide-wire completely, even if the catheter and guide-wire cling to the lumen or the shape of the catheter is irregular. Since only morphological operations are used to complete all processes, the calculation burden is reduced greatly.

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