Mechanism of action, benefits, and research gap in fermented soybean meal utilization as a high-quality protein source for livestock and poultry.

Animal nutritionists have incessantly worked towards providing livestock with high-quality plant protein feed resources. Soybean meal (SBM) has been an essential and predominantly adopted vegetable protein source in livestock feeding for a long time; however, several SBM antinutrients could potentially impair the animal's performance and growth, limiting its use. Several processing methods have been employed to remove SBM antinutrients, including fermentation with fungal or bacterial microorganisms. According to the literature, fermentation, a traditional food processing method, could improve SBM's nutritional and functional properties, making it more suitable and beneficial to livestock. The current interest in health-promoting functional feed, which can enhance the growth of animals, improve their immune system, and promote physiological benefits more than conventional feed, coupled with the ban on the use of antimicrobial growth promoters, has caused a renewed interest in the use of fermented SBM (FSBM) in livestock diets. This review details the mechanism of SBM fermentation and its impacts on animal health and discusses the recent trend in the application and emerging advantages to livestock while shedding light on the research gap that needs to be critically addressed in future studies. FSBM appears to be a multifunctional high-quality plant protein source for animals. Besides removing soybean antinutrients, beneficial bioactive peptides and digestive enzymes are produced during fermentation, providing probiotics, antioxidants, and immunomodulatory effects. Critical aspects regarding FSBM feeding to animals remain uncharted, such as the duration of fermentation, the influence of feeding on digestive tissue development, choice of microbial strain, and possible environmental impact.

Silibinin reduces in vitro methane production by regulating the rumen microbiome and metabolites.

This study used Silibinin as an additive to conduct fermentation experiments, wherein its effects on rumen gas production, fermentation, metabolites, and microbiome were analyzed in vitro. The silibinin inclusion level were 0 g/L (control group), 0.075 g/L, 0.15 g/L, 0.30 g/L, and 0.60 g/L (experimental group). Fermentation parameters, total gas production, carbon dioxide (CO2), methane (CH4), hydrogen (H2), and their percentages were determined. Further analysis of the rumen microbiome's relative abundance and α/ß diversity was performed on the Illumina NovaSeq sequencing platform. Qualitative and quantitative metabolomics analyses were performed to analyze the differential metabolites and metabolic pathways based on non-targeted metabolomics. The result indicated that with an increasing dose of silibinin, there was a linear reduction in total gas production, CO2, CH4, H2 and their respective percentages, and the acetic acid to propionic acid ratio. Concurrent with a linear increase in pH, when silibinin was added at 0.15 g/L and above, the total volatile fatty acid concentration decreased, the acetic acid molar ratio decreased, the propionic acid molar ratio increased, and dry matter digestibility decreased. At the same time, the relative abundance of Prevotella, Isotricha, Ophryoscolex, unclassified_Rotifera, Methanosphaera, Orpinomyces, and Neocallimastix in the rumen decreased after adding 0.60 g/L of silibinin. Simultaneously, the relative abundance of Succiniclasticum, NK4A214_group, Candidatus_Saccharimonas, and unclassified_Lachnospiraceae increased, altering the rumen species composition, community, and structure. Furthermore, it upregulated the ruminal metabolites, such as 2-Phenylacetamide, Phlorizin, Dalspinin, N6-(1,2-Dicarboxyethyl)-AMP, 5,6,7,8-Tetrahydromethanopterin, Flavin mononucleotide adenine dinucleotide reduced form (FMNH), Pyridoxine 5'-phosphate, Silibinin, and Beta-D-Fructose 6-phosphate, affecting phenylalanine metabolism, flavonoid biosynthesis, and folate biosynthesis pathways. In summary, adding silibinin can alter the rumen fermentation parameters and mitigate enteric methane production by regulating rumen microbiota and metabolites, which is important for developing novel rumen methane inhibitors.

Fine-grained weed recognition using Swin Transformer and two-stage transfer learning.

Weeding is very critical for agriculture due to its importance for reducing crop yield loss. Accurate recognition of weed species is one of the major challenges for achieving automatic and precise weeding. To improve the recognition performance of weeds and crops with similar visual characteristics, a fine-grained weed recognition method based on Swin Transformer and two-stage transfer learning is proposed in this study. First, the Swin Transformer network is introduced to learn the discriminative features that can distinguish subtle differences between visually similar weeds and crops. Second, a contrastive loss is applied to further enlarge the feature differences between different categories of weeds and crops. Finally, a two-stage transfer learning strategy is proposed to address the problem of insufficient training data and improve the accuracy of weed recognition. To evaluate the effectiveness of the proposed method, we constructed a private weed dataset (MWFI) with maize seedling and seven species of associated weeds that are collected in the farmland environment. The experimental results on this dataset show that the proposed method achieved the recognition accuracy, precision, recall, and F1 score of 99.18%, 99.33%, 99.11%, and 99.22%, respectively, which are superior to the performance of the state-of-the-art convolutional neural network (CNN)-based architectures including VGG-16, ResNet-50, DenseNet-121, SE-ResNet-50, and EfficientNetV2. Additionally, evaluation results on the public DeepWeeds dataset further demonstrate the effectiveness of the proposed method. This study can provide a reference for the design of automatic weed recognition systems.

Retinal Microaneurysms Detection Using Gradient Vector Analysis and Class Imbalance Classification.

Retinal microaneurysms (MAs) are the earliest clinically observable lesions of diabetic retinopathy. Reliable automated MAs detection is thus critical for early diagnosis of diabetic retinopathy. This paper proposes a novel method for the automated MAs detection in color fundus images based on gradient vector analysis and class imbalance classification, which is composed of two stages, i.e. candidate MAs extraction and classification. In the first stage, a candidate MAs extraction algorithm is devised by analyzing the gradient field of the image, in which a multi-scale log condition number map is computed based on the gradient vectors for vessel removal, and then the candidate MAs are localized according to the second order directional derivatives computed in different directions. Due to the complexity of fundus image, besides a small number of true MAs, there are also a large amount of non-MAs in the extracted candidates. Classifying the true MAs and the non-MAs is an extremely class imbalanced classification problem. Therefore, in the second stage, several types of features including geometry, contrast, intensity, edge, texture, region descriptors and other features are extracted from the candidate MAs and a class imbalance classifier, i.e., RUSBoost, is trained for the MAs classification. With the Retinopathy Online Challenge (ROC) criterion, the proposed method achieves an average sensitivity of 0.433 at 1/8, 1/4, 1/2, 1, 2, 4 and 8 false positives per image on the ROC database, which is comparable with the state-of-the-art approaches, and 0.321 on the DiaRetDB1 V2.1 database, which outperforms the state-of-the-art approaches.

Evaluation of crowded optic nerve head and small scleral canal in intrapapillary hemorrhage with adjacent peripapillary subretinal hemorrhage.

BACKGROUND: Intrapapillary hemorrhage with adjacent peripapillary subretinal hemorrhage (IHAPSH) is a clinical syndrome most commonly affecting myopic eyes with tilted discs that usually resolves spontaneously without treatment. Subretinal hemorrhage usually occurs peripapillary on the nasally adjacent side near the optic disc. The etiology of this condition is still unknown. The purpose of this study was to determine if a crowded optic nerve head and small scleral canal are involved in the pathogenetic mechanisms of IHAPSH. METHODS: Twelve subjects with IHAPSH diagnosed at the Affiliated Ophthalmology Hospital of the First Clinical College of Harbin Medical University and 24 control subjects were examined. The size of the inner aspect of the scleral canal and level of nerve fiber crowding of the optic nerve head were analyzed with optic nerve head analysis software packet of the Stratus Optical Coherence Tomography software and manual segmentation software. The Mann-Whitney U test and multiple comparisons (with the Bonferroni correction method) were performed. p values less than 0.002 (two-sided) were considered statistically significant. The area, perimeter, and the perimeter/area ratio of the optic disc, vertical and horizontal diameter of the inner aspect of the scleral canal, vertical integrated rim area (VIRA), and the rim area were calculated. RESULTS: The area and perimeter of the optic disc and the horizontal diameter of the inner aspect of the scleral canal were significantly lower in the affected and contralateral eyes of the subjects with IHAPSH than in the eyes of the controls. Conversely, the IHAPSH-affected and contralateral eyes had significantly higher perimeter/area ratio of the optic disc, VIRA, and rim area values than the control eyes. The VIRA and rim area were greater in the IHAPSH-affected eyes than in the contralateral eyes. CONCLUSIONS: Patients with IHAPSH have smaller optic discs and scleral canals than control subjects, with a higher level of nerve fiber crowding.