Smilax China L. polysaccharide prevents HFD induced-NAFLD by regulating hepatic fat metabolism and gut microbiota.

BACKGROUND: The increasing incidence of nonalcoholic fatty liver disease (NAFLD) has urged the development of new therapeutics. NAFLD is intimately linked to gut microbiota due to the hepatic portal system, and utilizing natural polysaccharides as prebiotics has become a prospective strategy for preventing NAFLD. Smilax china L. polysaccharide (SCP) possesses excellent hepatoprotective and anti-inflammatory activity. However, its protective effects on NAFLD remains unclear. PURPOSE: The goal of this study was to explore the protective effects of SCP on high-fat diet (HFD)-induced NAFLD mice by regulating hepatic fat metabolism and gut microbiota. METHODS: Extraction and isolation from Smilax china L. rhizome to obtain SCP. C57BL/6 J mice were distributed to six groups: Control (normal chow diet), HFD-fed mice were assigned to HFD, simvastatin (SVT), and low-, medium-, high-doses of SCP for 12 weeks. The body, liver, and different adipose tissues weights were detected, and lipids in serum and liver were assessed. RT-PCR and Western blot were used to detect the hepatic fat metabolism-related genes and proteins. Gut microbiota of cecum contents was profiled through 16S rRNA gene sequencing. RESULTS: SCP effectively reversed HFD-induced increase weights of body, liver, and different adipose tissues. Lipid levels of serum and liver were also significantly reduced after SCP intervention. According to the results of RT-PCR and western blot analysis, SCP treatment up-regulated the genes and proteins related to lipolysis were up-regulated, while lipogenesis-related genes and proteins were down-regulated. Furthermore, the HFD-induced dysbiosis of intestinal microbiota was similarly repaired by SCP intervention, including enriching beneficial bacteria and depleting harmful bacteria. CONCLUSION: SCP could effectively prevent HFD-induced NAFLD, might be considered as a prebiotic agent due to its excellent effects on altering hepatic fat metabolism and maintaining gut microbiota homeostasis.

Atroposelective Total Synthesis of Cihunamide B.

A short, atroposelective synthesis of cihunamide B (1) is reported. The feature of this report is the decagram-scale SNAr reaction of l-tryptophan derivatives, followed by atroposelective Larock macrocyclization. This strategy allowed the construction of a Trp-Trp cross-linkage with unprecedented atropisomerism. The atroposelectivity of this Larock macrocyclization has been investigated through a combination of experimental and computational chemistry, yielding detailed insights into the synthesis of biaryl linkages. It also enabled the concise synthesis of cihunamide B (1), which is expected to be a potential antibacterial agent.

An Image Detection Model for Aggressive Behavior of Group Sheep.

Sheep aggression detection is crucial for maintaining the welfare of a large-scale sheep breeding environment. Currently, animal aggression is predominantly detected using image and video detection methods. However, there is a lack of lightweight network models available for detecting aggressive behavior among groups of sheep. Therefore, this paper proposes a model for image detection of aggression behavior in group sheep. The proposed model utilizes the GhostNet network as its feature extraction network, incorporating the PWConv and Channel Shuffle operations into the GhostConv module. These additional modules improve the exchange of information between different feature maps. An ablation experiment was conducted to compare the detection effectiveness of the two modules in different positions. For increasing the amount of information in feature maps of the GhostBottleneck module, we applied the Inverted-GhostBottleneck module, which introduces inverted residual structure based on GhostBottleneck. The improved GhostNet lightweight feature extraction network achieves 94.7% Precision and 90.7% Recall, and its model size is only 62.7% of YOLOv5. Our improved model surpasses the original model in performance. Furthermore, it addresses the limitation of the video detection model, which was unable to accurately locate aggressive sheep. In real-time, our improved model successfully detects aggressive behavior among group sheep.

Short, Scalable Access to Pyrrovobasine.

A concise gram-scale synthesis of pyrrovobasine (1) is reported. Key transformations include a three-step decagram-scale synthesis of the tetracyclic compound, Mn-mediated direct radical cyclization, and the introduction of a naturally rare pyrraline structure. The synthesis is designed to be applicable to gram-scale synthesis using inexpensive and readily available reagents.

Lipopolysaccharide-induced persistent inflammation ameliorates fat accumulation by promoting adipose browning in vitro and in vivo.

This work aimed to explore whether the persistent inflammation induced by lipopolysaccharide (LPS) ameliorates fat accumulation by promoting adipose browning in vitro and in vivo. LPS over 1 ng/mL reduced lipid accumulation while increasing the expressions of specific genes involved in inflammation, mitochondrial biogenesis, and adipose browning in 3T3-L1 adipocytes. Moreover, LPS in intraperitoneal injection decreased white adipose tissue weight and elevated interscapular brown adipose tissue weight in mice. According to RT-PCR and western blot analysis results, the expressions of genes and proteins related to inflammation, mitochondrial biogenesis, lipolysis, and brown or beige markers in different tissues were elevated after LPS intervention. Cumulatively, LPS-induced persistent inflammation may potentially ameliorate fat accumulation by facilitating adipose browning in 3T3-L1 adipocytes and mice. These results offer new perspectives into the effect of persistent inflammation induced by LPS on regulating fat metabolism, thereby reducing fat accumulation by boosting adipose browning procedure.

Spatio-Temporal-Based Identification of Aggressive Behavior in Group Sheep.

In order to solve the problems of low efficiency and subjectivity of manual observation in the process of group-sheep-aggression detection, we propose a video streaming-based model for detecting aggressive behavior in group sheep. In the experiment, we collected videos of the sheep's daily routine and videos of the aggressive behavior of sheep in the sheep pen. Using the open-source software LabelImg, we labeled the data with bounding boxes. Firstly, the YOLOv5 detects all sheep in each frame of the video and outputs the coordinates information. Secondly, we sort the sheep's coordinates using a sheep tracking heuristic proposed in this paper. Finally, the sorted data are fed into an LSTM framework to predict the occurrence of aggression. To optimize the model's parameters, we analyze the confidence, batch size and skipping frame. The best-performing model from our experiments has 93.38% Precision and 91.86% Recall. Additionally, we compare our video streaming-based model with image-based models for detecting aggression in group sheep. In sheep aggression, the video stream detection model can solve the false detection phenomenon caused by head impact feature occlusion of aggressive sheep in the image detection model.

A Method to Predict CO2 Mass Concentration in Sheep Barns Based on the RF-PSO-LSTM Model.

In large-scale meat sheep farming, high CO2 concentrations in sheep sheds can lead to stress and harm the healthy growth of meat sheep, so a timely and accurate understanding of the trend of CO2 concentration and early regulation are essential to ensure the environmental safety of sheep sheds and the welfare of meat sheep. In order to accurately understand and regulate CO2 concentrations in sheep barns, we propose a prediction method based on the RF-PSO-LSTM model. The approach we propose has four main parts. First, to address the problems of data packet loss, distortion, singular values, and differences in the magnitude of the ambient air quality data collected from sheep sheds, we performed data preprocessing using mean smoothing, linear interpolation, and data normalization. Second, to address the problems of many types of ambient air quality parameters in sheep barns and possible redundancy or overlapping information, we used a random forests algorithm (RF) to screen and rank the features affecting CO2 mass concentration and selected the top four features (light intensity, air relative humidity, air temperature, and PM2.5 mass concentration) as the input of the model to eliminate redundant information among the variables. Then, to address the problem of manually debugging the hyperparameters of the long short-term memory model (LSTM), which is time consuming and labor intensive, as well as potentially subjective, we used a particle swarm optimization (PSO) algorithm to obtain the optimal combination of parameters, avoiding the disadvantages of selecting hyperparameters based on subjective experience. Finally, we trained the LSTM model using the optimized parameters obtained by the PSO algorithm to obtain the proposed model in this paper. The experimental results show that our proposed model has a root mean square error (RMSE) of 75.422 µg·m-3, a mean absolute error (MAE) of 51.839 µg·m-3, and a coefficient of determination (R2) of 0.992. The model prediction curve is close to the real curve and has a good prediction effect, which can be useful for the accurate prediction and regulation of CO2 concentration in sheep barns in large-scale meat sheep farming.

A Recognition Method of Ewe Estrus Crawling Behavior Based on Multi-Target Detection Layer Neural Network.

There are some problems with estrus detection in ewes in large-scale meat sheep farming: mainly, the manual detection method is labor-intensive and the contact sensor detection method causes stress reactions in ewes. To solve the abovementioned problems, we proposed a multi-objective detection layer neural network-based method for ewe estrus crawling behavior recognition. The approach we proposed has four main parts. Firstly, to address the problem of mismatch between our constructed ewe estrus dataset and the YOLO v3 anchor box size, we propose to obtain a new anchor box size by clustering the ewe estrus dataset using the K-means++ algorithm. Secondly, to address the problem of low model recognition precision caused by small imaging of distant ewes in the dataset, we added a 104 × 104 target detection layer, making the total target detection layer reach four layers, strengthening the model's ability to learn shallow information and improving the model's ability to detect small targets. Then, we added residual units to the residual structure of the model, so that the deep feature information of the model is not easily lost and further fused with the shallow feature information to speed up the training of the model. Finally, we maintain the aspect ratio of the images in the data-loading module of the model to reduce the distortion of the image information and increase the precision of the model. The experimental results show that our proposed model has 98.56% recognition precision, while recall was 98.04%, F1 value was 98%, mAP was 99.78%, FPS was 41 f/s, and model size was 276 M, which can meet the accurate and real-time recognition of ewe estrus behavior in large-scale meat sheep farming.

Asymmetric Synthesis of 2,2-Difluorotetrahydrofurans through Palladium-Catalyzed Formal [3+2] Cycloaddition.

The asymmetric synthesis of 2,2-difluorinated tetrahydrofurans was accomplished via enantioselective formal [3+2] cycloaddition catalyzed by palladium. The asymmetric reaction between gem-difluoroalkenes and racemic vinyl epoxides or vinylethylene carbonates resulted in the formation of enantioenriched 2,2-difluorotetrahydrofurans with an enantioselectivity up to 98 %. Notably, the reaction used the readily available (R)-BINAP as the ligand at a low loading and yielded a wide variety of difluorinated products in moderate to high yields. Both chiral diastereomers could be obtained in a single sequence.

N-Protecting group tuning of the enantioselectivity in Strecker reactions of trifluoromethyl ketimines to synthesize quaternary α-trifluoromethyl amino nitriles by ion pair catalysis.

An enantioselective Strecker reaction to construct trifluoromethylated quaternary stereocenters with N-PMP and unexplored N-Boc trifluoromethyl ketimines catalyzed using an organophosphine dual-reagent catalyst has been developed. The enantioselectivities of the corresponding products with the same catalyst could be switched by using different N-protecting groups (N-PMP or N-Boc). The trifluoromethyl amino nitriles were obtained in high yield and high enantioselectivity in a short time and could be easily converted to a variety of useful trifluoromethyl-containing compounds.

Asymmetric Total Synthesis of Vincadifformine Enabled by a Thiourea-Phosphonium Salt Catalyzed Mannich-Type Reaction.

An asymmetric total synthesis of vincadifformine is described. The limited tactics with chiral cation-directed catalysis in total synthesis inspired the development of our strategy for accessing this alkaloid in enantionrich form. The route features a thiourea-phosphonium salt catalyzed Mannich-type reaction, a phosphine-promoted aza-Morita-Baylis-Hillman reaction and a trifluoroacetic acid promoted deprotection/amidation cascade process.

FGL2 knockdown improves heart function through regulation of TLR9 signaling in the experimental autoimmune myocarditis rats.

Fibrinogen-like protein 2 (FGL2) is an important immune regulator of both innate and adaptive response. It is present on the surface of macrophages and endothelial cells, and can be constitutively secreted by CD4+CD8+ T cells. Previous studies showed that FGL2 is a potential target for the treatment of experimental autoimmune myocarditis. However, the molecular mechanism of the roles of FGL2 in experimental autoimmune myocarditis is poorly understood. Here, we silenced FGL2 gene by using FGL2-RNAi lentivirus to reveal the heart function in experimental autoimmune myocarditis rats. We found that the cardiac myosin of pigs' hearts induced Lewis rats to come into being as autoimmune myocarditis. TLR9 was upregulated in the heart of experimental autoimmune myocarditis rats. After primary immunization (21 day), the cardiac function of the myocarditis model group improved (P < 0.05). Significantly, the levels of INF-α and NF-κB in the FGL2-RNAi-treated group were lower compared to those in the myocarditis model (EAM) group (P < 0.05). Notably, the inflammation score correspondence with the protein and mRNA levels of TLR9 in myocardial tissues was markedly reduced compared to that in the EAM group (P < 0.05). These results support a role of FGL2 to alleviate inflammatory situation in the myocardium through regulation of the TLR9 signaling pathway in the experimental autoimmune myocarditis rats.