| 1611. |
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| 1612. |
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| 1613. |
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| 1614. |
- Sun, Chen, et al.
(författare)
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Polysaccharide-K (PSK) in Cancer : Old Story, New Possibilities?
- 2012
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Ingår i: Current Medicinal Chemistry. - 0929-8673. ; 19:5, s. 757-762
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Forskningsöversikt (refereegranskat)abstract
- Polysaccharide-K (PSK, Krestin) is one of the most commonly used medicinal mushroom extracts with a long history as an additive in cancer therapy in Asia, especially in Japan. PSK has a documented anti-tumor activity both in vitro and in vitro, in various types of cancers, including colorectal, gastric, breast, liver, pancreatic, and lung cancer. Despite PSK having been studied for about 40 years as an immune modulator and biological response modifier, the mechanisms of action by PSK have not yet been clearly and completely elucidated. This review aims to provide an up-to-date account for the effects of PSK in cancer with the hope of thereby providing an increased understanding of the molecular mechanisms of PSK and also its potential as an additive in modern cancer therapy.
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| 1615. |
- Sun, H., et al.
(författare)
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Corrected ERA5 Precipitation by Machine Learning Significantly Improved Flow Simulations for the Third Pole Basins
- 2022
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Ingår i: Journal of Hydrometeorology. - : American Meteorological Society. - 1525-755X .- 1525-7541. ; 23:10, s. 1663-1679
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Tidskriftsartikel (refereegranskat)abstract
- Precipitation is one of the most important atmospheric inputs to hydrological models. However, existing precipitation datasets for the Third Pole (TP) basins show large discrepancies in precipitation magnitudes and spatiotemporal patterns, which poses a great challenge to hydrological simulations in the TP basins. In this study, a gridded (10 km x 10 km) daily precipitation dataset is constructed through a random-forest-based machine learning algorithm (RF algorithm) correction of the ERA5 precipitation estimates based on 940 gauges in 11 upper basins of TP for 1951-2020. The dataset is evaluated by gauge observations at point scale and is inversely evaluated by the Variable Infiltration Capacity (VIC) hydrological model linked with a glacier melt algorithm (VIC-Glacier). The corrected ERA5 (ERA5_cor) agrees well with gauge observations after eliminating the severe overestimation in the original ERA5 precipitation. The corrections greatly reduce the original ERA5 precipitation estimates by 10%-50% in 11 basins of the TP and present more details on precipitation spatial variability. The inverse hydrological model evaluation demonstrates the accuracy and rationality, and we provide an updated estimate of runoff components contribution to total runoff in seven upper basins in the TP based on the VIC-Glacier model simulations with the ERA5_cor precipitation. This study provides good precipitation estimates with high spatiotemporal resolution for 11 upper basins in the TP, which are expected to facilitate the hydrological modeling and prediction studies in this high mountainous region. Significance StatementThe Third Pole (TP) is the source of water to the people living in the areas downstream. Precipitation is the key driver of the terrestrial hydrological cycle and the most important atmospheric input to land surface hydrological models. However, none of the current precipitation data are equally good for all the TP basins because of high variabilities in their magnitudes and spatiotemporal patterns, posing a great challenge to the hydrological simulation. Therefore, in this study, a gridded daily precipitation dataset (10 km x 10 km) is reconstructed through a random-forest-based machine learning algorithm correction of ERA5 precipitation estimates based on 940 gauges in 11 TP basins for 1951-2020. The data eliminate the severe overestimation of original ERA5 precipitation estimates and present more reasonable spatial variability, and also exhibit a high potential for hydrological application in the TP basins. This study provides long-term precipitation data for climate and hydrological studies and a reference for deriving precipitation in high mountainous regions with complex terrain and limited observations.
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| 1616. |
- Sun, Jia, et al.
(författare)
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Cathelicidins positively regulate pancreatic beta-cell functions
- 2016
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Ingår i: The FASEB Journal. - : Wiley. - 0892-6638 .- 1530-6860. ; 30:2, s. 884-894
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Tidskriftsartikel (refereegranskat)abstract
- Cathelicidins are pleiotropic antimicrobial peptides largely described for innate antimicrobial defenses and, more recently, immunomodulation. They are shown to modulate a variety of immune or nonimmune host cell responses. However, how cathelicidins are expressed by beta cells and modulate beta-cell functions under steady-state or proinflammatory conditions are unknown. We find that cathelicidin-related antimicrobial peptide (CRAMP) is constitutively expressed by rat insulinoma b-cell clone INS-1 832/13. CRAMP expression is inducible by butyrate or phenylbutyric acid and its secretion triggered upon inflammatory challenges by IL-1 beta or LPS. CRAMP promotes b-cell survival in vitro via the epidermal growth factor receptor (EGFR) and by modulating expression of antiapoptotic Bcl-2 family proteins: p-Bad, Bcl-2, and Bcl-xL. Also via EGFR, CRAMP stimulates glucose-stimulated insulin secretion ex vivo by rat islets. A similar effect is observed in diabetes-prone nonobese diabetic (NOD) mice. Additional investigation under inflammatory conditions reveals that CRAMP modulates inflammatory responses and beta-cell apoptosis, asmeasured by prostaglandin E2 production, cyclooxygenases (COXs), and caspase activation. Finally, CRAMP-deficient cnlp(-/-) mice exhibit defective insulin secretion, and administration of CRAMP to prediabetic NOD mice improves blood glucose clearance upon glucose challenge. Our finding suggests that cathelicidins positively regulate beta-cell functions and may be potentially used for intervening b-cell dysfunction-associated diseases.
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| 1617. |
- Sun, Mingyue, et al.
(författare)
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Out-of-order execution enabled deep reinforcement learning for dynamic additive manufacturing scheduling
- 2025
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Ingår i: Robotics and Computer-Integrated Manufacturing. - : Elsevier BV. - 0736-5845 .- 1879-2537. ; 91
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Tidskriftsartikel (refereegranskat)abstract
- Additive Manufacturing (AM) has revolutionized the production landscape by enabling on-demand customized manufacturing. However, the efficient management of dynamic AM orders poses significant challenges for production planning and scheduling. This paper addresses the dynamic scheduling problem considering batch processing, random order arrival and machine eligibility constraints, aiming to minimize total tardiness in a parallel non-identical AM machine environment. To tackle this problem, we propose the out-of-order enabled dueling deep Q network (O3-DDQN) approach. In the proposed approach, the problem is formulated as a Markov decision process (MDP). Three-dimensional features, encompassing dynamic orders, AM machines, and delays, are extracted using a ‘look around’ method to represent the production status at a rescheduling point. Additionally, five novel composite scheduling rules based on the out-of-order principle are introduced for selection when an AM machine completes processing or a new order arrives. Moreover, we design a reward function that is strongly correlated with the objective to evaluate the agent's chosen action. Experimental results demonstrate the superiority of the O3-DDQN approach over single scheduling rules, randomly selected rules, and the classic DQN method. The average improvement rate of performance reaches 13.09% compared to composite scheduling rules and random rules. Additionally, the O3-DDQN outperforms the classic DQN agent with a 6.54% improvement rate. The O3-DDQN algorithm improves scheduling in dynamic AM environments, enhancing productivity and on-time delivery. This research contributes to advancing AM production and offers insights into efficient resource allocation.
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| 1618. |
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| 1619. |
- Sun, S., et al.
(författare)
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A comprehensive risk assessment of Chinese high-speed railways affected by multiple meteorological hazards
- 2022
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Ingår i: Weather and Climate Extremes. - : Elsevier BV. - 2212-0947. ; 38
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Tidskriftsartikel (refereegranskat)abstract
- Meteorological hazards pose a significant risk to the operation and safety of the Chinese railway system. As China Railway High-speed (CRH) has become a vital part of the Chinese transportation infrastructure, an improved understanding of the spatial pattern of multiple hazards across the railway network is urgently needed, especially in the context of accelerated climate change. This study provides a spatial analysis of the dominant meteoro-logical hazards affecting the CRH network (i.e., gales, rainfall, and snow), in terms of both intensity and fre-quency, and identifies hazard zones according to CRH operating standards. Given that meteorological hazards can lead to speed limitation or disruption of CRH trains, a risk matrix model is developed based on hazard in-tensity and designated railway speed to comprehensively assess the risk level of CRH lines in China. Risk assessment indicates that CRH lines exposed to hazardous levels of gales, rainfall, and snow account for 6.0%, 29.3%, and 20.0% of the total line length, respectively, while 7.3% of CRH lines are exposed to multiple hazards. Meteorological risk maps for CRH operation reveal hotspot lines that require special adaptive or preventative measures, and emergency protocols to reduce potential losses and disruptions.
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| 1620. |
- Sun, S., et al.
(författare)
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Inhibition of the Activation and Recruitment of Microglia-Like Cells Protects Against Neomycin-Induced Ototoxicity
- 2015
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Ingår i: Molecular Neurobiology. - : Springer Science and Business Media LLC. - 0893-7648 .- 1559-1182. ; 51:1, s. 252-267
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Tidskriftsartikel (refereegranskat)abstract
- One of the most unfortunate side effects of aminoglycoside (AG) antibiotics such as neomycin is that they target sensory hair cells (HCs) and can cause permanent hearing impairment. We have observed HC loss and microglia-like cell (MLC) activation in the inner ear (cochlea) following neomycin administration. We focused on CX3CL1, a membrane-bound glycoprotein expressed on neurons and endothelial cells, as a way to understand how the MLCs are activated and the role these cells play in HC loss. CX3CL1 is the exclusive ligand for CX3CR1, which is a chemokine receptor expressed on the surface of macrophages and MLCs. In vitro experiments showed that the expression levels of CX3CL1 and CX3CR1 increased in the cochlea upon neomycin treatment, and CX3CL1 was expressed on HCs, while CX3CR1 was expressed on MLCs. When cultured with 1 mu g/mL exogenous CX3CL1, MLCs were activated by CX3CL1, and the cytokine level was increased in the cochleae leading to apoptosis in the HCs. In CX3CR1 knockout mice, a significantly greater number of cochlear HCs survived than in wild-type mice when the cochlear explants were cultured with neomycin in vitro. Furthermore, inhibiting the activation of MLCs with minocycline reduced the neomycin-induced HC loss and improved the hearing function in neomycin-treated mice in vivo. Our results demonstrate that CX3CL1-induced MLC activation plays an important role in the induction of HC death and provide evidence for CX3CL1 and CX3CR1 as promising new therapeutic targets for the prevention of hearing loss.
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