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http://dx.doi.org/10.23736/S0026-4806.23.08699-8 | DOI Listing |
Protein Sci
February 2025
IRR Chemistry Hub, Institute for Regeneration and Repair, The University of Edinburgh, Edinburgh, UK.
Super-resolution microscopy has revolutionized biological imaging, enabling the visualization of structures at the nanometer length scale. Its application in live cells, however, has remained challenging. To address this, we adapted LIVE-PAINT, an approach we established in yeast, for application in live mammalian cells.
View Article and Find Full Text PDFOphthalmic Physiol Opt
January 2025
Vision and Hearing Sciences Research Centre, Anglia Ruskin University, Cambridge, UK.
Purpose: Wearable electronic low vision enhancement systems (wEVES) improve visual function but are not widely adopted by people with vision impairment. Here, qualitative research methods were used to investigate the usefulness of wEVES for people with age-related macular degeneration (AMD) after an extended home trial.
Methods: Following a 12-week non-masked randomised crossover trial, semi-structured interviews were completed with 34 participants with AMD, 64.
Clin Genet
January 2025
Department of Medical Genetics, Medical Faculty, Aksaray University, Aksaray, Turkiye.
Inherited retinal diseases (IRDs) constitute a heterogeneous group of clinically and genetically diverse conditions, standing as a primary cause of visual impairment among individuals aged 15-45, with an estimated incidence of 1:2000. Our study aimed to comprehensively evaluate the genetic variants underlying IRDs in the Turkish population. This study included 50 unrelated Turkish IRD patients and their families.
View Article and Find Full Text PDFAnn Surg Oncol
January 2025
Department of Hepatopancreatobiliary and Liver Transplant Surgery, Queen Elizabeth Hospital, Birmingham, United Kingdom.
Eur J Nucl Med Mol Imaging
January 2025
Department of Nuclear Medicine, Xiangya Hospital, Central South University, No. 87 Xiangya Road, Changsha, Hunan, 410008, P.R. China.
Purpose: To develop and validate a prostate-specific membrane antigen (PSMA) PET/CT based multimodal deep learning model for predicting pathological lymph node invasion (LNI) in prostate cancer (PCa) patients identified as candidates for extended pelvic lymph node dissection (ePLND) by preoperative nomograms.
Methods: [Ga]Ga-PSMA-617 PET/CT scan of 116 eligible PCa patients (82 in the training cohort and 34 in the test cohort) who underwent radical prostatectomy with ePLND were analyzed in our study. The Med3D deep learning network was utilized to extract discriminative features from the entire prostate volume of interest on the PET/CT images.
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