Keratins are one of the main fluorophores of the skin. Keratinization disorders can lead to alterations in the optical properties of the skin. We set out to investigate a rare form of keratinopathic ichthyosis caused by mutation with two different optical imaging methods. We used a newly developed light emitting diode (LED) based device to analyze autofluorescence signal at 405 nm excitation and diffuse reflectance at 526 nm in vivo. Mean autofluorescence intensity of the hyperkeratotic palmar skin was markedly higher in comparison to the healthy control (162.35 vs. 51.14). To further assess the skin status, we examined samples from affected skin areas ex vivo by nonlinear optical microscopy. Two-photon excited fluorescence and second-harmonic generation can visualize epidermal keratin and dermal collagen, respectively. We were able to visualize the structure of the epidermis and other skin changes caused by abnormal keratin formation. Taken together, we were able to show that such imaging modalities are useful for the diagnosis and follow-up of keratinopathic diseases.
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http://dx.doi.org/10.3390/s21041105 | DOI Listing |
Sci Rep
December 2024
Department of Biomedical Engineering, Tufts University, 4 Colby Street, Medford, MA, 02155, USA.
We propose an overview of the Rytov approximation in diffuse optics of biological tissues, for the inverse and forward problems. First, we show a physical interpretation of the Rytov approximation as a type of partial pathlength (named fluence rate partial pathlength) which is distinct from the usual partial pathlength for reflectance measurements. Second, we study the accuracy of the Rytov approximation for the calculation of Jacobians considering absorption perturbations and reflectance measurements.
View Article and Find Full Text PDFSci Rep
December 2024
IRCCS SYNLAB SDN, Via E. Gianturco 113, 80143, Naples, Italy.
Uterine corpus endometrial carcinoma (EC) is one of the most common malignancies in the female reproductive system, characterized by tumor heterogeneity at both radiological and pathological scales. Both radiomics and pathomics have the potential to assess this heterogeneity and support EC diagnosis. This study examines the correlation between radiomics features from Apparent Diffusion Coefficient (ADC) maps and post-contrast T1 (T1C) images with pathomic features from pathology images in 32 patients from the CPTAC-UCEC database.
View Article and Find Full Text PDFPathophysiology
December 2024
Department of Obstetrics and Gynecology, Astana Medical University, Astana 010000, Kazakhstan.
Unlabelled: Histomorphometric measurements of the wall thickness and internal diameter of the macrovessels of the chorionic villi of placentas from pregnancies complicated by preeclampsia or fetal growth restriction in comparison with normotensive pregnancy.
Methods: The research included placentas from singleton pregnancies complicated by preeclampsia and/or fetal growth restriction, women delivered in medical institutions in Karaganda city (Kazakhstan). Placentas were divided into three groups: PE ( = 59), isolated FGR ( = 24), and PE with FGR ( = 41).
Mar Drugs
November 2024
Tissue Engineering Group, Department of Histology, Faculty of Medicine, University of Granada, E18016 Granada, Spain.
Cornea tissue engineering is strictly dependent on the development of biomaterials that fulfill the strict biocompatibility, biomechanical, and optical requirements of this organ. In this work, we generated novel biomaterials from the squid gladius (SG), and their application in cornea tissue engineering was evaluated. Results revealed that the native SG (N-SG) was biocompatible in laboratory animals, although a local inflammatory reaction was driven by the material.
View Article and Find Full Text PDFNeurol Sci
December 2024
Department of Radiology, The First People's Hospital of Foshan, #81 North Lingnan Avenue, Foshan, Guangdong, China.
Background: Identifying Parkinson's disease (PD) during its initial phases presents considerable hurdles for clinicians.
Purpose: To examine the feasibility and efficacy of a machine learning model based on quantitative multiparametric magnetic resonance imaging (MRI) features in identifying early-stage PD.
Methods: We recruited 33 participants, including 19 with early-stage PD, 14 with advanced-stage PD and 20 healthy control subjects.
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