Structured illumination microscopy (SIM) enables live-cell super-resolution imaging with wide field of view (FOV) and high imaging speed, but the illumination system is usually bulky. With the advantages of small structure and high efficiency, lattice patterns assisted by diffractive optical elements (DOEs) have been used for structured illumination in SIM. But it is still challenging to raise the spatial frequency of diffractive lattice patterns when using traditional DOE design method, and thus the super-resolution imaging performance is restricted. In this paper, we propose a novel design method for DOE to generate lattice patterns with spatial frequency close to the cut-off frequency. It is the first time to obtain a lattice pattern with such high spatial frequency by diffractive optics. Finally, the proposed SIM achieves a lateral resolution of 131 nm at 519 nm fluorescent light while maintaining an original size as a standard inverted fluorescence microscope by only inserting a single well-designed DOE in the illumination optical path, which may promote this compact SIM applied in super-resolution imaging field.
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http://dx.doi.org/10.1364/BOE.473899 | DOI Listing |
Sci Rep
January 2025
International Livestock Research Institute (ILRI), Human and Animal Health, Berlin, Germany.
Crimean Congo hemorrhagic fever (CCHF) is a re-emerging tick-borne zoonosis that is caused by CCHF virus (CCHFV). The geographical distribution of the disease and factors that influence its occurrence are poorly known. We analysed historical records on its outbreaks in various countries across the sub-Saharan Africa (SSA) to identify hotspots and determine socioecological and demographicfactors associated with these outbreaks.
View Article and Find Full Text PDFJ Neurosci
January 2025
Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center, F-75006 Paris, France.
Attention is key to perception and human behavior, and evidence shows that it periodically samples sensory information (<20Hz). However, this view has been recently challenged due to methodological concerns and gaps in our understanding of the function and mechanism of rhythmic attention. Here we used an intensive ∼22-hour psychophysical protocol combined with reverse correlation analyses to infer the neural representation underlying these rhythms.
View Article and Find Full Text PDFEnviron Res
January 2025
CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China. Electronic address:
This study encompasses the explication of systematic spatial distribution patterns and identification of hotspots of contaminants of emerging concern (CECs) across the network of rivers, including Yarlung Tsangpo River and its tributaries in Xizang Plateau. A total of 16 CECs were detected in wide range of frequencies and concentrations ranging from below limit of detection (BLD) - 163.13 ng/L across the river network, indicating widespread spatial heterogeneity.
View Article and Find Full Text PDFBrain Res Bull
January 2025
School of Life and Health Information Science and Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Institute for Advanced Sciences, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Guangyang Bay Laboratory, Chongqing Institute for Brain and Intelligence, Chongqing 400064, China. Electronic address:
Working memory, a fundamental cognitive function of the brain, necessitates the evaluation of cognitive load intensity due to limited cognitive resources. Optimizing cognitive load can enhance task performance efficiency by preventing resource waste and overload. Therefore, identifying working memory load is an essential area of research.
View Article and Find Full Text PDFComput Med Imaging Graph
January 2025
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; National Key Laboratory of Kidney Diseases, Beijing 100853, China. Electronic address:
In clinical optical molecular imaging, the need for real-time high frame rates and low excitation doses to ensure patient safety inherently increases susceptibility to detection noise. Faced with the challenge of image degradation caused by severe noise, image denoising is essential for mitigating the trade-off between acquisition cost and image quality. However, prevailing deep learning methods exhibit uncontrollable and suboptimal performance with limited interpretability, primarily due to neglecting underlying physical model and frequency information.
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