Neurons in the ectoderm of the perirhopalial tissue of the jellyfish Cyanea capillata were exposed and fixed for electron microscopy under conditions designed to minimize exocytosis of synaptic vesicles. The structure of the bidirectional chemical synapses that connect neurons was examined and the three-dimensional organization of these synapses was determined from reconstructions of serial sections. Synapses were characterized by the accumulation of a relatively few, large synaptic vesicles. These lie in a single layer against the terminal membrane of each terminal. The cytoplasmic side of the vesicles in any one terminal was covered by a single, large, perforated cisternal sheet. In addition, there were numerous smaller, bulbous cisternae that intermingled with the vesicles in the terminal. The structure of any one terminal was mirrored by that of the opposite terminal of the pair. The organization of these synapses is discussed from the viewpoint of cnidarian synapses in general.
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http://dx.doi.org/10.1002/syn.890020605 | DOI Listing |
Reprod Biomed Online
July 2024
Department of Gynaecology, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China. Electronic address:
Cilia in the fallopian tubes (CFT) play an important role in female infertility, but have not been explored comprehensively. This review reveals the detection techniques for CFT function and morphology, and the related analysis of female infertility and other gynaecological disorders. CFT differentiate from progenitor cells, and develop into primary cilia and motile cilia.
View Article and Find Full Text PDFCurr Diab Rep
December 2024
College of Nursing, University of Utah, 10 South 2000 East, Salt Lake City, UT, 84112, USA.
Purpose Of Review: Describe the connection between Deaf/hard of hearing (DHH) and diabetes, explain the bidirectional relationship of blind/low vision (BLV) and diabetes, characterize challenges DHH and BLV populations face when seeking healthcare regarding their diabetes management. Highlight the inaccessibility of diabetes technology in these populations. Provide best practices when communicating with DHH and BLV people in the clinical setting.
View Article and Find Full Text PDFSmall
December 2024
National Local Joint Engineering Laboratory for Key Materials of New Energy Storage Battery, Hunan Province Key Laboratory for Electrochemical Energy Storage and Conversion, School of Chemistry, Xiangtan University, Xiangtan, 411105, China.
The rapid catalytic conversion toward polysulfides is considered to be an advantageous approach to boost the reaction kinetics and inhibit the shuttle effect in lithium-sulfur (Li─S) batteries. However, the prediction of high catalytic activity Li─S catalysts has become challenging given the carelessness in the relationship between important electronic characteristics of catalysts and catalytic activity. Herein, the relationships between the D-band regulation of catalysts with reaction kinetics toward polysulfides are described.
View Article and Find Full Text PDFNat Sci Sleep
December 2024
Department of Orthodontics, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People's Republic of China.
Purpose: Sleep apnea (SA), associated with absent neural output, is characterised by recurrent episodes of hypoxemia and repeated arousals during sleep, resulting in decreased sleep quality and various health complications. Mitochondrial DNA copy number (mtDNA-CN), an easily accessible biomarker in blood, reflects mitochondrial function. However, the causal relationship between mtDNA-CN and SA remains unclear.
View Article and Find Full Text PDFWorld J Gastroenterol
December 2024
School of Computer Science Technology, Changchun University, Changchun 130022, Jilin Province, China.
Background: Wireless capsule endoscopy (WCE) has become an important noninvasive and portable tool for diagnosing digestive tract diseases and has been propelled by advancements in medical imaging technology. However, the complexity of the digestive tract structure, and the diversity of lesion types, results in different sites and types of lesions distinctly appearing in the images, posing a challenge for the accurate identification of digestive tract diseases.
Aim: To propose a deep learning-based lesion detection model to automatically identify and accurately label digestive tract lesions, thereby improving the diagnostic efficiency of doctors, and creating significant clinical application value.
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