Browsing by Author "Li R"

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    Dietary Supplementation of Yeast Culture Into Pelleted Total Mixed Rations Improves the Growth Performance of Fattening Lambs
    (Frontiers Media S.A., 2021-05) Song B; Wu T; You P; Wang H; Burke JL; Kang K; Yu W; Wang M; Li B; He Y; Huo Q; Li C; Tian W; Li R; Li J; Wang C; Sun X
    There is a growing interest in the use of yeast (Saccharomyces cerevisiae) culture (YC) for the enhancement of growth performance and general animal health. Grain-based pelleted total mixed rations (TMR) are emerging in intensive sheep farming systems, but it is uncertain if the process of pelleting results in YC becoming ineffective. This study aimed to examine the effects of YC supplemented to pelleted TMR at two proportions of corn in the diet on animal performance, feed digestion, blood parameters, rumen fermentation, and microbial community in fattening lambs. A 2 × 2 factorial design was adopted with two experimental factors and two levels in each factor, resulting in four treatments: (1) low proportion of corn in the diet (LC; 350 g corn/kg diet) without YC, (2) LC with YC (5 g/kg diet), (3) high proportion of corn in the diet (HC; 600 g corn/kg diet) without YC, and (4) HC with YC. Fifty-six 3-month-old male F2 hybrids of thin-tailed sheep and Northeast fine-wool sheep with a liveweight of 19.9 ± 2.7 kg were randomly assigned to the four treatment groups with an equal number of animals in each group. The results showed that live yeast cells could not survive during pelleting, and thus, any biological effects of the YC were the result of feeding dead yeast and the metabolites of yeast fermentation rather than live yeast cells. The supplementation of YC resulted in 31.1 g/day more average daily gain regardless of the proportion of corn in the diet with unchanged feed intake during the 56-day growth measurement period. The digestibility of neutral detergent fibre and acid detergent fibre was increased, but the digestibility of dry matter, organic matter, and crude protein was not affected by YC. The supplementation of YC altered the rumen bacterial population and species, but the most abundant phyla Bacteroidetes, Firmicutes, and Proteobacteria remained unchanged. This study indicates that YC products can be supplemented to pelleted TMR for improved lamb growth performance, although live yeast cells are inactive after pelleting. The improved performance could be attributed to improved fibre digestibility.
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    DiffusionDCI: A Novel Diffusion-Based Unified Framework for Dynamic Full-Field OCT Image Generation and Segmentation
    (IEEE Access, 2024) Yang B; Li J; Wang J; Li R; Gu K; Liu B; Militello C
    Rapid and accurate identification of cancerous areas during surgery is crucial for guiding surgical procedures and reducing postoperative recurrence rates. Dynamic Cell Imaging (DCI) has emerged as a promising alternative to traditional frozen section pathology, offering high-resolution displays of tissue structures and cellular characteristics. However, challenges persist in segmenting DCI images using deep learning methods, such as color variation and artifacts between patches in whole slide DCI images, and the difficulty in obtaining precise annotated data. In this paper, we introduce a novel two-stage framework for DCI image generation and segmentation. Initially, the Dual Semantic Diffusion Model (DSDM) is specifically designed to generate high-quality and semantically relevant DCI images. These images not only serve as an effective means of data augmentation to assist downstream segmentation tasks but also help in reducing the reliance on expensive and hard-to-obtain large annotated medical image datasets. Furthermore, we reuse the pretrained DSDM to extract diffusion features, which are then infused into the segmentation network via a cross-attention alignment module. This approach enables our network to capture and utilize the characteristics of DCI images more effectively, thereby significantly enhancing segmentation results. Our method was validated on the DCI dataset and compared with other methods for image generation and segmentation. Experimental results demonstrate that our method achieves superior performance in both tasks, proving the effectiveness of the proposed model.