Thin, uniformly fluorescing reference layers can be used to characterize the imaging conditions in confocal, or more general, sectioning microscopy. Through-focus datasets of such layers obtained by standard microscope routines provide the basis for the approach. A set of parameters derived from these datasets is developed for defining a number of relevant sectioned imaging properties. The main characteristics of a particular imaging situation can then be summarized in a Sectioned Imaging Property-chart or SIPchart. We propose the use of such charts for the characterization of imaging properties in confocal and multiphoton microscopy. As such, they can be the basis for comparison of sectioned imaging condition characteristics, quality control, maintenance or reproduction of sectioned imaging conditions and other applications. Such charts could prove useful in documenting the more relevant properties of the instrumentation used in microscopy studies. The method carries the potential to provide the basis for a general characterization of sectioned imaging conditions as the layers employed can be characterized and fabricated to standard specifications. A limited number of such thin, uniformly fluorescing layers is available from our group for this purpose. Extension of the method to multiphoton microscopy is discussed.
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Acta Bioeng Biomech
June 2024
4Department of Pediatric Dentistry and Preclinical Dentistry, Wroclaw Medical University, Wrocław, Poland.
: Caries or iatrogenic thermal trauma of the teeth have a significant impact on the dental pulp structure connected with stimulation of angiogenesis and lymphangiogenesis. Therefore, the aim of the study was to identify the difference in the rate of heat dissipation by vessels present in the dental pulp. : Freshly extracted healthy ( = 10) and carious ( = 14) molars and premolars were cut on a diamond saw and subjected to active thermographic examination and then subjected to lymphoscintigraphy and X-ray examination.
View Article and Find Full Text PDFRadiology
January 2025
From the Department of Radiology, University of Washington, UW Medical Center-Montlake, Seattle, Wash (D.M.); Department of Radiology, OncoRad/Tumor Imaging Metrics Core (TIMC), University of Washington, Seattle, Wash (D.M.); Department of Radiology and Imaging Sciences, Emory University, Atlanta, Ga (M.v.A.); Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, the Netherlands (M.H.); Department of Radiology, Mayo Clinic, Rochester, Minn (T.L., E.E.W.); Departments of Cardiology and Radiology, Royal Brompton Hospital, London, United Kingdom (E.D.N.); School of Biomedical Engineering and Imaging Sciences, King's College, London, United Kingdom (E.D.N.); Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Ill (B.D.A.); Department of Radiology, University of Cagliari, Cagliari, Italy (L.S.); Department of Radiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1 Postbus 30 001, 9700 RB Groningen, the Netherlands (R.V.); Department of Medical Imaging, University Medical Imaging Toronto, University of Toronto, Toronto, Ontario, Canada (K.H.); and Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada (K.H.).
Artificial intelligence (AI) offers promising solutions for many steps of the cardiac imaging workflow, from patient and test selection through image acquisition, reconstruction, and interpretation, extending to prognostication and reporting. Despite the development of many cardiac imaging AI algorithms, AI tools are at various stages of development and face challenges for clinical implementation. This scientific statement, endorsed by several societies in the field, provides an overview of the current landscape and challenges of AI applications in cardiac CT and MRI.
View Article and Find Full Text PDFAnal Chem
January 2025
State Key Laboratory of Chemical Resource Engineering, College of Chemistry, Beijing University of Chemical Technology, Beijing 100029, China.
The spontaneous aggregation of amyloid-β (Aβ) leads to neuronal cell death in the brain and causes the development of Alzheimer's disease (AD). The efficient detection of the aggregation state of Aβ holds significant promise for the early diagnosis and subsequent treatment of this neurodegenerative disorder. Currently, most of the fluorescent probes used for the detection of Aβ fibrils share similar recognition moieties, such as the ,-dimethylamino group, ,-diethylamino group, and piperidyl group.
View Article and Find Full Text PDFCurr Protoc
January 2025
Department of Molecular Pneumology, Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg, Universitätsklinikum Erlangen, Erlangen, Germany.
Understanding the dynamic pathophysiology of diseases in the lung, such as asthma and chronic asthma, chronic obstructive pulmonary disease, and lung cancer, is crucial for the treatment, analysis, and outcome of these diseases. Unlike other traditional models, we suggest a protocol that is sustainable and reproducible and offers different analysis methods while maintaining in vivo lung architecture and immune dynamics. This protocol allows one to study the pathophysiological changes, including changes to the immune cells, cytokines, and mediators, in 30 precision-cut lung slices from a single murine lung.
View Article and Find Full Text PDFJ Dent Sci
January 2025
School of Dentistry and Institute of Oral Medicine, National Cheng Kung University, Tainan, Taiwan.
Background/purpose: The efficacy of riboflavin-ultraviolet-A (RF-UVA) treatment in crosslinking collagen and improving dentin bonding has been proven. However, biodegradation of the hybrid layer may compromise the bonding. The purpose of this study was to evaluate different RF-UVA treatments regarding their ability to preserve dentin bonding from enzymatic digestion.
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