EFFECTS OF POLYSACCHARIDES FROM GYNOSTEMMA PENTAPHYLLUM (THUNB.), MAKINO ON PHYSICAL FATIGUE

Background: Gynostemma pentaphyllum (Thunb.) Makino has been reported to have a wide range of health benefits in Chinese herbal medicines. Polysaccharides from Gynostemma pentaphyllum (PGP), has been identified as one of the active ingredients responsible for its biological activities. Although many pharmacological activities of PGP have received a great deal of attention, there is limited evidence for the anti-fatigue effects of PGP. The purpose of this study was to investigate the effects of polysaccharides from PGP on physical fatigue. Materials and method: The rats were divided into four groups, with 10 animals per group: control (C), group, low-treated (LT), group, medium-treated (MT), group, and high-treated (HT), group. The C group received distilled water, while LT, MT and HT groups were given various doses of PGP (100, 200, 400 mg/kg• d). After 30 days, forced swimming test was carried out in an acrylic plastic pool, then the exhaustive swimming time of rats and some biochemical parameters related to fatigue were measured. The data obtained showed that PGP could extend the exhaustive swimming time of the rats, as well as decrease the blood lactic acid (BLA), and blood urea nitrogen (BUN), concentrations, and increase the hemoglobin, liver glycogen and muscle glycogen concentrations. Result: The data obtained showed that different doses of PGP could extend the exhaustive swimming time of the rats, as well as decrease the BLA and BUN concentrations, and increase the hemoglobin, liver glycogen and muscle glycogen concentrations, which suggests that PGP had significant anti-fatigue effects on rats. Conclusion: PGP may be of use as a potential anti-fatigue agent, but there is a need for further research on long-term use in order to show its positive effects on physical fatigue

Patch Spatio-Temporal Relation Prediction for Video Anomaly Detection

Video Anomaly Detection (VAD), aiming to identify abnormalities within a specific context and timeframe, is crucial for intelligent Video Surveillance Systems. While recent deep learning-based VAD models have shown promising results by generating high-resolution frames, they often lack competence in preserving detailed spatial and temporal coherence in video frames. To tackle this issue, we propose a self-supervised learning approach for VAD through an inter-patch relationship prediction task. Specifically, we introduce a two-branch vision transformer network designed to capture deep visual features of video frames, addressing spatial and temporal dimensions responsible for modeling appearance and motion patterns, respectively. The inter-patch relationship in each dimension is decoupled into inter-patch similarity and the order information of each patch. To mitigate memory consumption, we convert the order information prediction task into a multi-label learning problem, and the inter-patch similarity prediction task into a distance matrix regression problem. Comprehensive experiments demonstrate the effectiveness of our method, surpassing pixel-generation-based methods by a significant margin across three public benchmarks. Additionally, our approach outperforms other self-supervised learning-based methods

Mitigating environmental impacts of milk production via integrated maize silage planting and dairy cow breeding system: A case study in China

peer reviewedEnvironmental impacts of milk production are depending on the production efficiency of livestock and cropland. A mode of integrated maize silage planting and dairy breeding system (IPBS) has been widely promoted in China, as a promising way to recycle manure, reduce chemical fertilizer consumption and improve soil quality. However, quantitative environmental impacts and mitigation potential of this system remains unclear. In this study, based on life cycle assessment (LCA), environmental performance of non-IPBS and IPBS were compared: non-IPBS only involved dairy cow breeding, whereas maize silage planting was incorporated in IPBS. Results indicated that, although 60% of the surveyed dairy farms adopted IPBS, the self-sufficiency rate of maize silage was 57%. Compared with non-IPBS, IPBS had apparent potential in reducing global warming potential (−14%), acidification potential (−10%), eutrophication potential (−18%), non-renewable energy use (−10%), water use (−8%) and land use (−13%). It is estimated that, in China, 81% of dairy farms could adopt IPBS, resulting in a reduction of approximately 21% in greenhouse gas (GHG) emissions to compared with current situation, but the premise is that 2.0 million ha cropland should be applied for maize silage cultivation. Interestingly, environmental performance of IPBS was affected by the self-sufficiency rate of maize silage and restricted by milk yield and maize silage yield. Thus, mitigation of environmental impacts of milk production could be realized by combining a short-term strategy of increasing maize silage planting area in dairy farms and a long-term plan for technological improvements in the yield of crop and milk

DCPoint: global-local dual contrast for self-supervised representation learning of 3D point clouds

In recent years, 3D vision has gained increasing prominence in practical applications such as autonomous driving and robotics. However, the scarcity of large labeled point cloud datasets continues to be a bottleneck for deep networks. Self-supervised representation learning (SRL) has emerged as an effective approach to alleviate this issue by pre-training general feature encoders without requiring human annotations. Existing contrastive SRL methods for 3D point clouds have predominantly concentrated on object representations from a global or point perspective. They overlook essential local geometry information, thereby constraining the generalizability of pre-trained models. To address these challenges, we propose a local contrast module as an intermediate level between the scene and point levels. It is then integrated with a global contrast module to form a dual contrast method known as DCPoint. The local contrast module operates on point-wise representations of objects and designs contrastive pairs based on the spatial information of point clouds. It effectively addresses the challenges posed by the sparsity and irregularity of point clouds and imperfect partition issues. The point-wise local contrast module aims to enhance the internal connections between the components within the point cloud, while the global contrast module introduces semantic information about individual instances. Experimental results demonstrate the effectiveness of DCPoint across various downstream tasks on synthetic and real-world datasets. It consistently outperforms previously reported SRL methods and the randomly initialized counterparts. Additionally, the proposed local contrast module can enhance the performances of other SRL methods

Molecular Ecology of Pyrethroid Knockdown Resistance in Culex pipiens pallens Mosquitoes

Pyrethroid insecticides have been extensively used in China and worldwide for public health pest control. Accurate resistance monitoring is essential to guide the rational use of insecticides and resistance management. Here we examined the nucleotide diversity of the para-sodium channel gene, which confers knockdown resistance (kdr) in Culex pipiens pallens mosquitoes in China. The sequence analysis of the para-sodium channel gene identified L1014F and L1014S mutations. We developed and validated allele-specific PCR and the real-time TaqMan methods for resistance diagnosis. The real-time TaqMan method is more superior to the allele-specific PCR method as evidenced by higher amplification rate and better sensitivity and specificity. Significant positive correlation between kdr allele frequency and bioassay-based resistance phenotype demonstrates that the frequency of L1014F and L1014S mutations in the kdr gene can be used as a molecular marker for deltamethrin resistance monitoring in natural Cx. pipiens pallens populations in the East China region. The laboratory selection experiment found that L1014F mutation frequency, but not L1014S mutation, responded to deltamethrin selection, suggesting that the L1014F mutation is the key mutation conferring resistance to deltamethrin. High L1014F mutation frequency detected in six populations of Cx. pipens pallens suggests high prevalence of pyrethroid resistance in Eastern China, calling for further surveys to map the resistance in China and for investigating alternative mosquito control strategies