We investigate the in-plane confinement effect of two graphene layers on the diffusion behaviour of water sub-monolayers using molecular dynamics simulations. An unexpected fast diffusion state with giant anisotropy is observed when the two confining graphene walls have certain shifts applied to their relative positions. The phenomenon is mainly attributed to the smooth one-dimensional potential channels produced by the composition effect of the potential energy landscapes of the two graphene walls, and the concerted motion of water molecules due to hydrogen bonding. Unique duality in the diffusion mechanism is observed in the fast diffusion state, as is ballistic motion along the potential channels and Fickian diffusion across such channels. The smooth potential channels can be created in certain directions simply by shifting the confining walls, which provides a novel measure to manipulate the motion of confined molecules in real-time.
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http://dx.doi.org/10.1088/0957-4484/24/50/505504 | DOI Listing |
Chem Commun (Camb)
January 2025
Marshall Laboratory of Biomedical Engineering, International Cancer Center, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, Laboratory of Evolutionary Theranostics (LET), School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen 518055, China.
The introduction of fluorescence imaging (FLI) in near-infrared II sub-channels (NIR-IIb, 1500-1700 nm) has revolutionized the ability to explore complex patho-physiological settings . Despite the transformative potentials, the development of organic NIR IIb dyes encounters considerable difficulties, and only a limited number of such fluorophores have been developed so far. This review systematically introduces design strategies of organic NIR-IIb fluorophores classified by molecular scaffolds, mainly including cyanine dyes and D-A-D small molecule dyes.
View Article and Find Full Text PDFIr J Med Sci
January 2025
Department of Clinical Pharmacy, College of Pharmacy, King Khalid University, Abha, Saudi Arabia.
Aim: This study aimed to identify the most commonly used tools by recent pharmacy graduates who successfully passed the Saudi Pharmacists Licensure Examination (SPLE). It also sought to evaluate which tools were perceived as the most useful and representative of the exam content, while considering their monetary value and offering recommendations for future candidates.
Methods: A cross-sectional design was used, involving licensed pharmacists who graduated in 2019 or later and had successfully passed the SPLE.
In Vitro Model
February 2024
IFIBYNE-UBA-CONICET, Buenos Aires, Argentina.
In this Highlights article, we present insights into the use of simple cell lines in neuroinflammation research, highlighting key findings from our recent investigations. Simple cell lines, including HEK, PC12, SHSY5Y, and N2a cells, provide valuable insights into critical signaling pathways and hidden facets of the neuroinflammatory landscape. Focusing on specific outcomes, including the impact of interleukin-6 (IL-6) and acid-sensing ion channels (ASIC1a), the study sheds light on neuroinflammatory processes.
View Article and Find Full Text PDFFront Nutr
January 2025
Nutrition Institute, Ljubljana, Slovenia.
Objective: Bakery products are considered as one of main dietary sources of sodium/salt in Slovenia. Our main objective was to assess the salt content in bread in Slovenia, focusing into different bread categories and sales channels. The data collected in 2022 was compared with year 2012.
View Article and Find Full Text PDFFront Neurorobot
January 2025
College of Artificial Intelligence, Taiyuan University of Technology, Jinzhong, Shanxi, China.
Accurate building segmentation has become critical in various fields such as urban management, urban planning, mapping, and navigation. With the increasing diversity in the number, size, and shape of buildings, convolutional neural networks have been used to segment and extract buildings from such images, resulting in increased efficiency and utilization of image features. We propose a building semantic segmentation method to improve the traditional Unet convolutional neural network by integrating attention mechanism and boundary detection.
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