Locating a molecule within a cell using protein-tagging and immunofluorescence is a fundamental technique in cell biology, whereas in three-dimensional electron microscopy, locating a subunit within a macromolecular complex remains challenging. Recently, we developed a new structural labeling method for cryo-electron tomography by taking advantage of the biotin-streptavidin system, and have intensively used this method to locate a number of proteins and protein domains in cilia and flagella. In this review, we summarize our findings on the three-dimensional architecture of the axoneme, especially the importance of coiled-coil proteins. In addition, we provide an overview of the technical aspects of our structural labeling method.
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http://dx.doi.org/10.1093/jmicro/dfx018 | DOI Listing |
Anal Chim Acta
February 2025
Food Inspection and Quarantine Technology Center of Shenzhen Customs, Shenzhen Academy of Inspection and Quarantine, Shenzhen, 518045, PR China.
Background: Ochratoxin A (OTA) is toxic secondary metabolites produced by fungi and can pose a serious threat to food safety and human health. Due to the high stability and toxicity, OTA contamination in agricultural products is of great concern. Therefore, the development of a highly sensitive and reliable OTA detection method is crucial to ensure food safety.
View Article and Find Full Text PDFExp Eye Res
January 2025
Department of Ophthalmology, Zhongshan Hospital, Fudan University, Shanghai, China. Electronic address:
The study aimed to compare the effects of different types of excimer laser keratectomy on rabbit corneas and to identify the optimal disease model for corneal ectasia. Additionally, investigating the structural and molecular alterations in the novel disease model helped explore the mechanisms underlying biomechanical cues in corneal ectasia. 2.
View Article and Find Full Text PDFJ Colloid Interface Sci
January 2025
Department of Oncology, the First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, PR China. Electronic address:
In recent years, the chiral biological effects of nanomedicines have garnered significant interest. Research has focused on understanding how material chirality affects cellular transcription and metabolism. Stress granules, which are membraneless organelles formed through liquid-liquid phase separation of G3BP1 proteins and related compartments, have been extensively studied and are closely associated with cellular damage repair and metabolism.
View Article and Find Full Text PDFInt Immunopharmacol
January 2025
Infectious Diseases Laboratory, Campus Ministro Reis Velloso, Federal University of Parnaíba Delta, 64202-020 Parnaíba, PI, Brazil. Electronic address:
Visceral leishmaniasis is a systemic disease that affects various internal organs and represents the most severe and fatal form of leishmaniasis. Conventional treatment presents significant challenges, such as prolonged management in hospital settings, high toxicity, and an increasing growing number of cases of resistance. In previous studies, our research group demonstrated the effective and selective activity of the 2-amino-thiophene derivative SB-83 in preclinical models of cutaneous leishmaniasis.
View Article and Find Full Text PDFMol Divers
January 2025
Key Laboratory for Macromolecular Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an, 710119, People's Republic of China.
Molecular Property Prediction (MPP) is a fundamental task in important research fields such as chemistry, materials, biology, and medicine, where traditional computational chemistry methods based on quantum mechanics often consume substantial time and computing power. In recent years, machine learning has been increasingly used in computational chemistry, in which graph neural networks have shown good performance in molecular property prediction tasks, but they have some limitations in terms of generalizability, interpretability, and certainty. In order to address the above challenges, a Multiscale Molecular Structural Neural Network (MMSNet) is proposed in this paper, which obtains rich multiscale molecular representations through the information fusion between bonded and non-bonded "message passing" structures at the atomic scale and spatial feature information "encoder-decoder" structures at the molecular scale; a multi-level attention mechanism is introduced on the basis of theoretical analysis of molecular mechanics in order to enhance the model's interpretability; the prediction results of MMSNet are used as label values and clustered in the molecular library by the K-NN (K-Nearest Neighbors) algorithm to reverse match the spatial structure of the molecules, and the certainty of the model is quantified by comparing virtual screening results across different K-values.
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