The parasitic helminthTrichinella spiralis, which poses a serious health risk to animals and humans, can be found worldwide. Recent findings indicate that a rare type of gut epithelial cell, tuft cells, can detect the helminth, triggering type 2 immune responses. However, the underlying molecular mechanisms remain to be fully understood. Here we show that both excretory–secretory products (E–S) and extract ofT. spiraliscan stimulate the release of the cytokine interleukin 25 (IL-25) from the mouse small intestinal villi and evoke calcium responses from tuft cells in the intestinal organoids, which can be blocked by a bitter-taste receptor inhibitor, allyl isothiocyanate. Heterologously expressed mouse Tas2r bitter-taste receptors, the expression of which is augmented during tuft-cell hyperplasia, can respond to the E–S and extract as well as to the bitter compound salicin whereas salicin in turn can induce IL-25 release from tuft cells. Furthermore, abolishment of the G-protein γ13 subunit, application of the inhibitors for G-protein αo/i, Gβγ subunits, and phospholipase Cβ2 dramatically reduces the IL-25 release. Finally, tuft cells are found to utilize the inositol triphosphate receptor type 2 (Ip3r2) to regulate cytosolic calcium and thus Trpm5 activity, while potentiation of Trpm5 by a sweet-tasting compound, stevioside, enhances tuft cell IL-25 release and hyperplasia in vivo. Taken together,T. spiralisinfection activates a signaling pathway in intestinal tuft cells similar to that of taste-bud cells, but with some key differences, to initiate type 2 immunity.

The wide variety of crops in the image of agricultural products and the confusion with the surrounding environment information makes it difficult for traditional methods to extract crops accurately and efficiently. In this paper, an automatic extraction algorithm is proposed for crop images based on Mask RCNN. First, the Fruits 360 Dataset label is set with Labelme. Then, the Fruits 360 Dataset is preprocessed. Next, the data are divided into a training set and a test set. Additionally, an improved Mask RCNN network model structure is established using the PyTorch 1.8.1 deep learning framework, and path aggregation and features are added to the network design enhanced functions, optimized region extraction network, and feature pyramid network. The spatial information of the feature map is saved by the bilinear interpolation method in ROIAlign. Finally, the edge accuracy of the segmentation mask is further improved by adding a micro-fully connected layer to the mask branch of the ROI output, employing the Sobel operator to predict the target edge, and adding the edge loss to the loss function. Compared with FCN and Mask RCNN and other image extraction algorithms, the experimental results demonstrate that the improved Mask RCNN algorithm proposed in this paper is better in the precision, Recall, Average precision, Mean Average Precision, and F1 scores of crop image extraction results.

Taste and smell are very important chemical senses that provide indispensable information on food quality, potential mates and potential danger. In recent decades, much progress has been achieved regarding the underlying molecular and cellular mechanisms of taste and odor senses. Recently, biosensors have been developed for detecting odorants and tastants as well as for studying ligand-receptor interactions. This review summarizes the currently available biosensing approaches, which can be classified into two main categories: in vitro and in vivo approaches. The former is based on utilizing biological components such as taste and olfactory tissues, cells and receptors, as sensitive elements. The latter is dependent on signals recorded from animals' signaling pathways using implanted microelectrodes into living animals. Advantages and disadvantages of these two approaches, as well as differences in terms of sensing principles and applications are highlighted. The main current challenges, future trends and prospects of research in biomimetic taste and odor sensors are discussed.

Inflammatory bowel disease (IBD) is one of the immune-related gastrointestinal disorders, including ulcerative colitis and Crohn's disease, that affects the life quality of millions of people worldwide. IBD symptoms include abdominal pain, diarrhea, and rectal bleeding, which may result from the interactions among gut microbiota, food components, intestinal epithelial cells, and immune cells. It is of particular importance to assess how each key gene expressed in intestinal epithelial and immune cells affects inflammation in the colon. G protein-coupled taste receptors, including G protein subunit α-gustducin and other signaling proteins, have been found in the intestines. Here, we use α-gustducin as a representative and describe a dextran sulfate sodium (DSS)-induced IBD model to evaluate the effect of gustatory gene mutations on gut mucosal immunity and inflammation. This method combines gene knockout technology with the chemically induced IBD model, and thus can be applied to assess the outcome of gustatory gene nullification as well as other genes that may exuberate or dampen the DSS-induced immune response in the colon. Mutant mice are administered with DSS for a certain period during which their body weight, stool, and rectal bleeding are monitored and recorded. At different timepoints during administration, some mice are euthanized, then the sizes and weights of their spleens and colons are measured and gut tissues are collected and processed for histological and gene expression analyses. The data show that the α-gustducin knockout results in excessive weight loss, diarrhea, intestinal bleeding, tissue damage, and inflammation vs. wild-type mice. Since the severity of induced inflammation is affected by mouse strains, housing environment, and diet, optimization of DSS concentration and administration duration in a pilot experiment is particularly important. By adjusting these factors, this method can be applied to assess both anti-and proinflammatory effects.

Introduction: Chuanxiong, a traditional Chinese medicine, has been proved to treat a variety of cardiovascular and cerebrovascular diseases by promoting angiogenesis. However, the mechanisms of Chuanxiong’s pro-angiogenesis is currently unknown. This study aimed to uncover the effect and mechanisms of Chuanxiong promoting angiogenesis in vivo and in vitro.Methods: First, potential targets were predicted by network pharmacology analysis, and PPI network was established and the pathways were enriched. Then, the chorioallantoic membrane test on quails was applied to assess the proangiogenic effects in vivo. As well, to evaluate the effects in vitro, real-time PCR, western blot analysis, the scratch test, and the tube formation experiment were used. Subsequently, the major metabolic pathways were analyzed using non-targeted metabolomics.Results: As a result of network pharmacological analysis, 51 collective targets of Chuanxiong and angiogenesis were identified, which are mainly associated with PI3K/AKT/Ras/MAPK pathway. And the biological verification results showed that Chuanxiong could increase the vessel numbers and vessel area in qCAM models. Meanwhile, Chuanxiong contributed to HUVEC proliferation, tube formation, migration, by encouraging scratch healing rates and boosting tube branch points. In addition, the levels of VEGFR2, MAPK and PI3K were elevated compared to the control group. The western blot analysis also confirmed Chuanxiong could promote an increase in AKT, FOXO1 and Ras. Furtheremore, metabolomic results showed that the proangiogenic effect of Chuanxiong is associated with glycine, serine and threonine metabolism.Discussion: In conclusion, this study clarified that Chuanxiong could promote angiogenesis in vivo and in vitro via regulating PI3K/AKT/Ras/MAPK pathway.