Amygdalin suppresses the proliferation, migration and EMT of gastric cancer cells by inhibiting TGF-β/Smad signal pathway

Purpose: To investigate the effects of amygdalin on the proliferation, motility and epithelial mesenchymal transformation (EMT) of gastric cancer cells and to elucidate the operating mechanisms of action.Methods: Gastric cancer AGS cells were treated with amygdalin (2.5, 5 and 10 mg/L). MTT and colony formation assays were used to investigate the effect of amygdalin on gastric cancer cell proliferation, while wound healing and Transwell assays were also carried out to determine its effect on the motility of gastric cancer cells. Immunoblot assays were used to investigate the effects of amygdalin on epithelial mesenchymal transformation (EMT) process and TGF-β/Smad pathway in gastric cancer cells.Results: Treatment with amygdalin suppressed the proliferation of gastric cancer AGS cells (p < 0.05). Amygdalin suppressed the migration and invasion of AGS cells in vitro (p < 0.05). Additionally, amygdalin suppressed epithelial mesenchymal transformation (EMT) in AGS cells, and suppressed TGF-β/Smad pathway (p < 0.05), thereby suppressing growth, motility, and EMT in AGS cells.Conclusion: Amygdalin may be useful for the treatment of gastric cancer; however, further studies are required ascertain this

Lugrandoside attenuates spinal cord injury by targeting peli1 and TLR4/NF-κB pathway to exert anti-inflammatory and anti-apoptotic effects

Purpose: To investigate the curative effect and mechanism of lugrandoside (LG) on spinal cord injury (SCI).Methods: We probed the expression of Pellino1 (peli1) in microglia and spinal cord tissues withdifferent treatments of LG. Lipopolysaccharide (LPS) was used to activate the microglia. Furthermore, rats were used to establish SCI model, and LG, at low and high concentrations, was administered to injured animals to ascertain whether LG exerted a therapeutic effect on SCI.Results: LG inhibited the activation and recruitment of glial cells by acting as a negative regulator of glial inflammation, and this reverse the targeting of peli1 and TLR4/NF-κB pathway. Furthermore, the in vivo data showed that LG exerted a neuroprotective effect, following SCI, via anti-inflammatory and antiapoptotic effects. Furthermore, Peli1 and TLR4/NF-κB were suppressed by LG stimuli.Conclusion: These results suggest that LG protects neural tissue against neuroinflammation and apoptosis by suppressing TLR4/NF-κB pathway and negatively targeting peli1. The findings may provide new insights into the treatment of spinal cord injury

From NeRFLiX to NeRFLiX++: A General NeRF-Agnostic Restorer Paradigm

Neural radiance fields (NeRF) have shown great success in novel view synthesis. However, recovering high-quality details from real-world scenes is still challenging for the existing NeRF-based approaches, due to the potential imperfect calibration information and scene representation inaccuracy. Even with high-quality training frames, the synthetic novel views produced by NeRF models still suffer from notable rendering artifacts, such as noise and blur. To address this, we propose NeRFLiX, a general NeRF-agnostic restorer paradigm that learns a degradation-driven inter-viewpoint mixer. Specially, we design a NeRF-style degradation modeling approach and construct large-scale training data, enabling the possibility of effectively removing NeRF-native rendering artifacts for deep neural networks. Moreover, beyond the degradation removal, we propose an inter-viewpoint aggregation framework that fuses highly related high-quality training images, pushing the performance of cutting-edge NeRF models to entirely new levels and producing highly photo-realistic synthetic views. Based on this paradigm, we further present NeRFLiX++ with a stronger two-stage NeRF degradation simulator and a faster inter-viewpoint mixer, achieving superior performance with significantly improved computational efficiency. Notably, NeRFLiX++ is capable of restoring photo-realistic ultra-high-resolution outputs from noisy low-resolution NeRF-rendered views. Extensive experiments demonstrate the excellent restoration ability of NeRFLiX++ on various novel view synthesis benchmarks.Comment: 17 pages, 16 figures. Project Page: https://redrock303.github.io/nerflix_plus/. arXiv admin note: text overlap with arXiv:2303.0691

Geraniin inhibits bladder cancer cell growth via regulation of PI3K/AKT signaling pathways

Purpose: The effect of geraniin on human bladder transitional carcinoma was not clear, this study was thus intended to reveal it and reveal the mechanism. Methods: T24 cells were treated with 5, 10, and 20 μM of geraniin and the viability and apoptosis of T24 cells were determined using thiazolyl blue tetrazolium bromide (MTT) assay and flow cytometry. The protein expression levels of Cyclin D1, p21, BAL-2, BAX, cleaved caspase-3 and PI3K/AKT pathway were evaluated using western blot. Results: Geraniin decreased T24 cell viability and induced T24 cell cycle arrest. The proportion of T24 cells in S phase was decreased by geraniin. Besides, geraniin promoted T24 cell apoptosis and regulated PI3K/AKT pathway. Conclusion: Geraniin appears to regulate bladder cancer cell growth by decreasing the levels of PI3K and AKT phosphorylation. Thus, this agent may be useful in the management of bladder cancer Keywords: Geraniin, T24 cells, Apoptosis, PI3K/AKT signalin

Computational prediction of type III secreted proteins from gram-negative bacteria

Abstract Background Type III secretion system (T3SS) is a specialized protein delivery system in gram-negative bacteria that injects proteins (called effectors) directly into the eukaryotic host cytosol and facilitates bacterial infection. For many plant and animal pathogens, T3SS is indispensable for disease development. Recently, T3SS has also been found in rhizobia and plays a crucial role in the nodulation process. Although a great deal of efforts have been done to understand type III secretion, the precise mechanism underlying the secretion and translocation process has not been fully understood. In particular, defined secretion and translocation signals enabling the secretion have not been identified from the type III secreted effectors (T3SEs), which makes the identification of these important virulence factors notoriously challenging. The availability of a large number of sequenced genomes for plant and animal-associated bacteria demands the development of efficient and effective prediction methods for the identification of T3SEs using bioinformatics approaches. Results We have developed a machine learning method based on the N-terminal amino acid sequences to predict novel type III effectors in the plant pathogen Pseudomonas syringae and the microsymbiont rhizobia. The extracted features used in the learning model (or classifier) include amino acid composition, secondary structure and solvent accessibility information. The method achieved a precision of over 90% on P. syringae in a cross validation study. In combination with a promoter screen for the type III specific promoters, this classifier trained on the P. syringae data was applied to predict novel T3SEs from the genomic sequences of four rhizobial strains. This application resulted in 57 candidate type III secreted proteins, 17 of which are confirmed effectors. Conclusion Our experimental results demonstrate that the machine learning method based on N-terminal amino acid sequences combined with a promoter screen could prove to be a very effective computational approach for predicting novel type III effectors in gram-negative bacteria. Our method and data are available to the public upon request

Microhabitat Segregation of Parapatric Frogs in the Qinling Mountains

Coexistence mechanisms for species with similar ecological traits and overlapping geographic distributions are basic questions in ecology and evolutionary biology. Specific habitat requirements often limit distribution range as well as facilitate partitioning resource utilization in ecological similar species. Understanding niche segregation and differences in microhabitat utilization can contribute to identifying coexistence mechanisms between parapatric species. Feirana quadranus and F. taihangnica are two closely related frog species with parapatric geographic ranges and an elongated contact zone within the Qinling Mountains, which is an important watershed for East Asia. Here, we analysed the difference in microhabitat utilization between the two frog species and explored the key ecological factors that induced their microhabitat differentiation based on quadrats sampled in the contact zone. Our comparison of twenty environmental variables showed that both species used microhabitats with alkalescent warm water and gentle slope conditions. The principal component analysis indicated that climate-related variables, vegetation conditions, and river width were the important factors for microhabitat utilization of these species. These findings contribute to our understanding on the coexistence mechanisms of these two related and parapatric Asian mountain frog species. This study can also be helpful for identifying target habitats to conduct conservation actions and management strategies effectively in the face of environmental changes