Substituting Fish Meal with Tubiechong (Eupolyphaga sinensis) By-Product in the Diets of Largemouth Bass (Micropterus salmoides): Effects on Growth, Meat Quality, and Liver Health.

A feeding trial was conducted to evaluate the effect of replacing 0% (control), 10% (T10), 20% (T20), 30% (T30), and 40% (T40) fish meal with a Tubiechong (Eupolyphaga sinensis) by-product in largemouth bass (Micropterus salmoides). Triplicate groups of 30 fish (5.36 ± 0.01 g) were fed two times daily to apparent satiation for 60 days. The experimental results showed that the Tubiechong by-product could improve the growth performance of largemouth bass by increasing the FBW, WGR, and SGR until the replacement ratio was 40%. The quadratic regression analysis showed that the proportion of the Tubiechong by-product was 20.79% and 20.91%, respectively, when WGR and SGR were the best. Concurrently, the meat quality in the replacement groups was higher, specifically, the lightness and white values were higher, and the water loss rates were lower (P < 0.05) than that in the control group. Moreover, the changes of the activities of CAT and GSH in the liver and T-AOC and GSH in serum could reveal the antioxidant capacity improvement of fish by the Tubiechong by-product. In the study, the replacement groups had lower T-CHO and HDL-C in serum (P < 0.05), indicating that the Tubiechong by-product had an active role in improving blood lipid and regulating lipid metabolism. Simultaneously, the replacement groups had a normal structure with central hepatocytes' nuclei and deviated from the center partly, while most of the hepatocytes were swollen in the control group with nuclear degeneration. The results showed that the Tubiechong by-product had a positive effect on the liver health of fish. Conclusively, the present study indicated that the partial dietary replacement of fish meal using the Tubiechong by-product (for up to 40% replacement level) in the diet of largemouth bass not only caused no adverse effects on fish health but also improved the growth performance, meat quality, antioxidant capacity, and hepatic health and is conducive to supplying nutritious, high-quality, and healthy aquatic products.

Potential of Chinese Yam (Dioscorea polystachya Turczaninow) By-Product as a Feed Additive in Largemouth Bass (Micropterus salmoides): Turning Waste into Valuable Resources.

Chinese yam (Dioscorea polystachya Turczaninow) by-product produced in the water extraction process is commonly directly discarded resulting in a waste of resources and environmental pollution. However, the value of Chinese yam by-product which still contains effective ingredients is far from being fully realized; hence, it has the potential to be a safe and effective feed additive in aquaculture. To investigate the impacts of Chinese yam by-product on growth performance, antioxidant ability, histomorphology, and intestinal microbiota of Micropterus salmoides, juvenile fish (initial weight 13.16 ± 0.05 g) were fed diets supplemented with 0% (control), 0.1% (S1), 0.4% (S2), and 1.6% (S3) of Chinese yam by-product for 60 days. The results showed that no significant difference was found in weight gain, specific growth rate, and survival among all the experimental groups (P > 0.05). Feed conversion ratios of the S1 and S3 groups were significantly lower than those in the control group (P < 0.05). SOD activity of the S3 group and GSH contents of Chinese yam by-product groups were significantly higher than those in the control group (P < 0.05). MDA levels of the S2 and S3 groups were significantly lower than those in the control group and the S1 group (P < 0.05). Besides, Chinese yam by-product could protect liver and intestine health, as well as increase the abundance of beneficial bacteria and decrease the abundance of potential pathogens. This study suggests that Chinese yam by-product has the potential to be used as a functional feed additive in aquaculture, providing a reference for efficient recovery and utilization of by-products from plant sources during processing and culturing high-quality aquatic products.

Cell image instance segmentation based on PolarMask using weak labels.

PURPOSE: A PolarMask-based method for blood cell contour segmentation is proposed. The method is divided into two parts. One part is a weak label-based model pretraining method, which uses weak labels to train the model and obtain a pretraining weight. The training speed and accuracy of the segmentation model are accelerated. The other part is based on the PolarMask method to segment the white and red blood cells in blood cells and can obtain smoother cell contours. Thus, it improves the accuracy of blood cell segmentation. Our method can help medical personnel identify the number of cells and cell shape quickly, which reduces the workload for medical personnel. METHODS: We improve PolarMask to make it more suitable for blood cell contour segmentation, and the improved method can be divided into two parts. In the first part, we use a weakly labeled dataset with the labeling type of bounding boxes for pretraining and then use the labels of the segmentation type for transfer learning of the cell segmentation model. In the second part, we add a smoothing constraint loss to the loss function of the mask to smoothen the segmented cell contours. We add the SE attention mechanism in the backbone network (ResNet18) to further improve the segmentation accuracy. RESULTS: Our method is mainly used for the segmentation of blood cell (erythrocyte and leukocyte) contours. Our method improves average precision (AP) by 8.4% and AP50 by 0.6% compared with PolarMask. The most significant improvement is in AP75, which improves by 8.8%. CONCLUSION: Our method models blood cell contours based on PolarMask and uses a weakly labeled training model to obtain pretrained weights that can segment red and white blood cells. Our method effectively improves the accuracy of the model in segmenting blood cells, and the segmented blood cell contours are smoother.

Review of research on the instance segmentation of cell images.

The instance segmentation of cell images is the basis for conducting cell research and is of great importance for the study and diagnosis of pathologies. To analyze current situations and future developments in the field of cell image instance segmentation, this paper first systematically reviews image segmentation methods based on traditional and deep learning methods. Then, from the three aspects of cell image weak label extraction, cell image instance segmentation, and cell internal structure segmentation, deep-learning-based cell image segmentation methods are analyzed and summarized. Finally, cell image instance segmentation is summarized, and challenges and future developments are discussed.

Microplastics as Contaminants in Water Bodies and Their Threat to the Aquatic Animals: A Mini-Review.

Microplastics (MPs), which are particles with a diameter of less than 5 mm, have been extensively studied due to their serious global pollution. Typically, MPs in water originate from terrestrial input. A number of studies have reported the presence of MPs as a stressor in water environments worldwide, and their potential threat to the aquatic animals, affecting the growth, oxidative stress responses, body composition, histopathology, intestinal flora, and immune and reproduction systems. During the plastic degradation process, a large variety of toxic substances are released. MPs have been proposed to be the carriers of toxic chemicals and harmful microorganisms. A study of the literature on MP pollution and stress on the aquatic animals associated with MPs was carried out.