The influence of bile acids homeostasis by cryptotanshinone-containing herbs

Background: Herbs might affect the homeostasis of bile acids through influence of multiple metabolic pathways of bile acids. Aim: The present study aims to investigate the inhibition of cryptotanshinone towards the glucuronidation of LCA, trying to indicate the possible influence of cryptotanshinone-containing herbs towards the homeostasis of bile acids. Methods: The LCA-3-glucuronidation and LCA-24-glucuronidation reaction was monitored by LC-MS. Results: Initial screening showed that 100 μM of cryptotanshinone inhibited LCA-24-glucuronidation and LCA-3-glucuronidation reaction activity by 82.6% and 79.1%, respectively. This kind of inhibition behaviour exerted cryptotanshinone concentrations-dependent and LCA concentrations-independent inhibition behaviour. Conclusion: All these data indicated the possibility of cryptotanshinone’s influence towards the bile acids metabolism and homeostasis of bile acids.Keywords: herbs, lithocholic acid (LCA), homeostasisAfrican Health sciences Vol 14 No. 1 March 201

Symphonize 3D Semantic Scene Completion with Contextual Instance Queries

3D Semantic Scene Completion (SSC) has emerged as a nascent and pivotal task for autonomous driving, as it involves predicting per-voxel occupancy within a 3D scene from partial LiDAR or image inputs. Existing methods primarily focus on the voxel-wise feature aggregation, while neglecting the instance-centric semantics and broader context. In this paper, we present a novel paradigm termed Symphonies (Scene-from-Insts) for SSC, which completes the scene volume from a sparse set of instance queries derived from the input with context awareness. By incorporating the queries as the instance feature representations within the scene, Symphonies dynamically encodes the instance-centric semantics to interact with the image and volume features while avoiding the dense voxel-wise modeling. Simultaneously, it orchestrates a more comprehensive understanding of the scenario by capturing context throughout the entire scene, contributing to alleviating the geometric ambiguity derived from occlusion and perspective errors. Symphonies achieves a state-of-the-art result of 13.02 mIoU on the challenging SemanticKITTI dataset, outperforming existing methods and showcasing the promising advancements of the paradigm. The code is available at \url{https://github.com/hustvl/Symphonies}.Comment: Technical report. Code and models at: https://github.com/hustvl/Symphonie

Efficient Multi-scale Network with Learnable Discrete Wavelet Transform for Blind Motion Deblurring

Coarse-to-fine schemes are widely used in traditional single-image motion deblur; however, in the context of deep learning, existing multi-scale algorithms not only require the use of complex modules for feature fusion of low-scale RGB images and deep semantics, but also manually generate low-resolution pairs of images that do not have sufficient confidence. In this work, we propose a multi-scale network based on single-input and multiple-outputs(SIMO) for motion deblurring. This simplifies the complexity of algorithms based on a coarse-to-fine scheme. To alleviate restoration defects impacting detail information brought about by using a multi-scale architecture, we combine the characteristics of real-world blurring trajectories with a learnable wavelet transform module to focus on the directional continuity and frequency features of the step-by-step transitions between blurred images to sharp images. In conclusion, we propose a multi-scale network with a learnable discrete wavelet transform (MLWNet), which exhibits state-of-the-art performance on multiple real-world deblurred datasets, in terms of both subjective and objective quality as well as computational efficiency

MobileInst: Video Instance Segmentation on the Mobile

Video instance segmentation on mobile devices is an important yet very challenging edge AI problem. It mainly suffers from (1) heavy computation and memory costs for frame-by-frame pixel-level instance perception and (2) complicated heuristics for tracking objects. To address those issues, we present MobileInst, a lightweight and mobile-friendly framework for video instance segmentation on mobile devices. Firstly, MobileInst adopts a mobile vision transformer to extract multi-level semantic features and presents an efficient query-based dual-transformer instance decoder for mask kernels and a semantic-enhanced mask decoder to generate instance segmentation per frame. Secondly, MobileInst exploits simple yet effective kernel reuse and kernel association to track objects for video instance segmentation. Further, we propose temporal query passing to enhance the tracking ability for kernels. We conduct experiments on COCO and YouTube-VIS datasets to demonstrate the superiority of MobileInst and evaluate the inference latency on one single CPU core of Snapdragon 778G Mobile Platform, without other methods of acceleration. On the COCO dataset, MobileInst achieves 31.2 mask AP and 433 ms on the mobile CPU, which reduces the latency by 50% compared to the previous SOTA. For video instance segmentation, MobileInst achieves 35.0 AP on YouTube-VIS 2019 and 30.1 AP on YouTube-VIS 2021. Code will be available to facilitate real-world applications and future research.Comment: Accepted by AAAI 2024 Main Track; Code will be release

Microbial diversity of intestinal contents and mucus in yellow catfish (Pelteobagrus fulvidraco)

In this study, traditional culture-based techniques and the 16S rDNA sequencing method were used to investigate the microbial community of the intestinal contents and mucosal layer in the intestine of yellow catfish (Pelteobagrus fulvidraco). Eleven phylotypes were detected from culturable microbiota, and their closest relatives were Plesiomonas, Yersinia, Enterobacter, Shewanella, Aeromonas, Vibrio, and Myroides. Forty-four phylotypes were retrieved from 100 positive clones from intestinal contents (library C), and 21 phylotypes were detected in the 57 positive clones from intestinal mucus (library M), most of which were affiliated with Proteobacteria (>50% of the total). However, the bacterial groups OP10 and Actinobacteria detected in library C were not found in library M, suggesting that the abundance and diversity of bacterial populations in mucus might be different from the microbiota in gut contents, and that some microbial species poorly colonized the gut mucosal layer. (C) 2010 Published by Elsevier B.V

The influence of bile acids homeostasis by cryptotanshinone-containing herbs

Background: Herbs might affect the homeostasis of bile acids through influence of multiple metabolic pathways of bile acids. Objective:To investigate the inhibition of cryptotanshinone towards the glucuronidation of LCA, trying to indicate the possible influence of cryptotanshinone-containing herbs towards the homeostasis of bile acids. Methods:The LCA-3-glucuronidation and LCA-24-glucuronidation reaction was monitored by LC-MS. Results:Initial screening showed that 100 μM of cryptotanshinone inhibited LCA-24-glucuronidation and LCA-3-glucuro-nidation reaction activity by 82.6% and 79.1%, respectively. This kind of inhibition behaviour exerted cryptotanshinone concentrations-dependent and LCA concentrations-independent inhibition behaviour. Conclusion: All these data indicated the possibility of cryptotanshinone’s influence towards bile acids metabolism and homeostasis of bile acids

The Responses of Sediment Bacterial Communities in Chinese Mitten Crab (<i>Eriocheir sinensis</i>) Culture Ponds to Changes in Physicochemical Properties Caused by Sediment Improvement

The interaction between nutrients, heavy metals, and sediment bacterial communities play a key role in the health of crabs and the biogeochemical cycles of aquaculture systems. However, the effects of sediment improvement activities in crab culture on nutrients and heavy metals and the response of bacterial communities to the relevant changes are unclear. In this study, 24 water and sediment samples were collected from two aquaculture sites (total of 12 ponds, 6 at each site). High-throughput sequencing was used to determine the structure of the bacterial community and the diversity in water and sediment samples. The relationship between nutrients, heavy metals, and bacterial communities and the changes of the three before and after the improvement of the sediment were analyzed. The results showed that Proteobacteria, Bacteroidetes, Acidobacteria, Chloroflexi, and Firmicutes were predominant at the phylum level of sediment. Sediment improvement has an effect on NH4+-N, sulfide, total organic carbon (TOC), and heavy metals in sediments to varying degrees. In addition, redundancy analysis found that NH4+-N, NO3−-N, TP, and heavy metals were key drivers in crab culture pond sediments. The results of functional prediction showed that carbon, nitrogen, and sulfur metabolism were the dominant processes in the two crab farming areas. Overall, changes in nutrients and heavy metals caused by sediment improvement further affected the structure and function of bacterial communities and may affect biogeochemical cycles. Our study has deepened the understanding of the effects of sediment improvement on nutrients, heavy metals, and bacterial communities in crab culture ponds

Anti-Cancer Activity of Porphyran and Carrageenan from Red Seaweeds

Seaweeds are some of the largest producers of biomass in the marine environment and are rich in bioactive compounds that are often used for human and animal health. Porphyran and carrageenan are natural compounds derived from red seaweeds. The former is a characteristic polysaccharide of Porphyra, while the latter is well known from Chondrus, Gigartina, and various Eucheuma species, all in Rhodophyceae. The two polysaccharides have been found to have anti-cancer activity by improving immunity and targeting key apoptotic molecules and therefore deemed as potential chemotherapeutic or chemopreventive agents. This review attempts to review the current study of anti-cancer activity and the possible mechanisms of porphyran and carrageenan derived from red seaweeds to various cancers, and their cooperative actions with other anti-cancer chemotherapeutic agents is also discussed

Organic carbon sink dynamics and carbon sink-source balance in global lakes during the Anthropocene

The carbon burial and greenhouse gas emissions of lakes are pivotal in the global carbon cycle to offset or accelerate global warming. However, their balance or the magnitude of anthropogenic increase of carbon burial remains uncertain in global lakes. Here, we quantified the carbon sink dynamics and the sink-source balance in global lakes with effect size metrics, that is, the log-response ratio of organic carbon burial between post-1950 and pre-1900 periods and the carbon balance ratio between carbon burial and greenhouse gas emissions, respectively. The organic carbon burial ratios revealed an average increase of 2.44 times in carbon burial rates during the Anthropocene, while the carbon balance ratios were negative in 82.68% of lakes, indicating that most lakes had lower burial rates than emission rates and acted as carbon sources rather than carbon sinks. The organic carbon burial ratios exhibited a significantly decreasing latitudinal trend and were mainly influenced by its trophic state with the explained variation of 44.79%. They were also indirectly influenced by climate, lake morphometry and catchment properties through their interactions with the lake’s trophic state. The carbon balance ratios however showed nonsignificant latitudinal trend. They were primarily affected by lake catchment properties with the explained variation of 26.21% and were also indirectly affected by climate variables via the interactions with catchment properties. Overall, our study highlights that human activities such as lake eutrophication and catchment changes have altered the carbon sink and source in global lakes during the Anthropocene, and are essential drivers for future evaluations of lake carbon budgets