Semi-supervised tissue segmentation from histopathological images with consistency regularization and uncertainty estimation.

Pathologists have depended on their visual experience to assess tissue structures in smear images, which was time-consuming, error-prone, and inconsistent. Deep learning, particularly Convolutional Neural Networks (CNNs), offers the ability to automate this procedure by recognizing patterns in tissue images. However, training these models necessitates huge amounts of labeled data, which can be difficult to come by due to the skill required for annotation and the unavailability of data, particularly for rare diseases.

Large scale mortality in cultured Nile tilapia (): natural co-infection with and .

Background: Nile tilapia is a highly valuable fish in the aquaculture sector. A culture farm has reported heavy mortalities of tilapia.

Aims: The present study aimed to identify the etiological agent responsible for the heavy mortality in cage cultured tilapia.

Aeromonas species obtained from different farmed aquatic species in India and Taiwan show high phenotypic relatedness despite species diversity.

Objectives: Aeromonads cause severe diseases in farmed aquatic organisms. Herein, we examined 28 isolates causing disease in farmed aquatic organisms from India (n = 24) and Taiwan (n = 4) to gain insight of their genotypic and phenotypic properties.

Results: API 20NE biochemical phenotyping showed ≥ 90% similarity classifying all isolates as Aeromonas hydrophila.

First report of the infectious spleen and kidney necrosis virus (ISKNV) infection in ornamental fishes in India.

Infectious spleen and kidney necrosis virus (ISKNV), a member of family iridoviridae, reported for the first time in a wide range of ornamental fish species in India. Significant mortalities during the year 2018-19 were reported from a number of retailers in the region with various clinical signs. The samples of moribund, dead and apparently healthy ornamental fishes were collected from retailers, located in three districts of Karnataka, India.