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Background: Transplantation as a therapeutic strategy for inherited retinal degeneration has been historically viewed to restore vision as a method by replacing the lost retinal cells and attempting to reconstruct the neural circuitry with stem cells, progenitor cells and mature neural retinal cells.
Methods And Findings: We present evidence for an alternative strategy aimed at preventing the secondary loss of cones, the most crucial photoreceptors for vision, by transplanting normal photoreceptors cells into the eye of the P23H rat, a model of dominant retinitis pigmentosa. We carried out transplantation of photoreceptors or total neural retina in 3-month-old P23H rats and evaluated the function and cell counts 6 months after surgery. In both groups, cone loss was significantly reduced (10%) in the transplanted eyes where the cone outer segments were found to be considerably longer. This morphological effect correlated with maintenance of the visual function of cones as scored by photopic ERG recording, but more precisely with an increase in the photopic b-wave amplitudes by 100% and 78% for photoreceptor transplantation and whole retinal transplantation respectively.
Conclusions: We demonstrate here that the transplanted tissue prevents the loss of cone function, which is further translated into cone survival.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2957406 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0013469 | PLOS |
Driven by eutrophication and global warming, the occurrence and frequency of harmful cyanobacteria blooms (CyanoHABs) are increasing worldwide, posing a serious threat to human health and biodiversity. Early warning enables precautional control measures of CyanoHABs within water bodies and in water works, and it becomes operational with high frequency in situ data (HFISD) of water quality and forecasting models by machine learning (ML). However, the acceptance of early warning systems by end-users relies significantly on the interpretability and generalizability of underlying models, and their operability.
View Article and Find Full Text PDFIEEE Trans Neural Netw Learn Syst
September 2025
Temporal modeling plays an important role in the effective adaption of the powerful pretrained text-image foundation model into text-video retrieval. However, existing methods often rely on additional heavy trainable modules, such as transformer or BiLSTM, which are inefficient. In contrast, we avoid introducing such heavy components by leveraging frozen foundation models.
View Article and Find Full Text PDFNaunyn Schmiedebergs Arch Pharmacol
September 2025
Department of Pharmacy, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Maternity and Child Health Hospital, Fujian Medical University, #18 Daoshan Road, Fuzhou, Fujian, 350001, China.
Postpartum hemorrhage (PPH) is a life-threatening obstetric complication. We aimed to identify the drugs that associated with PPH based on the FDA Adverse Event Reporting System (FAERS) data, providing scientific evidence for targeted prevention of drug-related PPH risk factors. Data from 2004Q1 to 2025Q1 were extracted from FAERS, and disproportionality analysis was performed to identify potential drug signals.
View Article and Find Full Text PDFJ Food Sci
September 2025
Department of Food Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, UKM, Bangi, Selangor Darul Ehsan, Malaysia.
Advanced intelligent systems are becoming a significant trend, especially in the classification of tropical fruits due to their unique flavor and taste. As one of the most popular tropical fruits worldwide, pineapple (Ananas comosus) has a great chemical composition and is high in nutritional value. A non-destructive method for the determination of pineapple varieties was developed, which utilized thermal imaging and deep learning techniques.
View Article and Find Full Text PDFJ Pain Res
September 2025
Radiology Department, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People's Republic of China.
Purpose: Previous studies have revealed alterations of the functional connectivity of the brain networks in ankylosing spondylitis (AS). Fractional amplitude of low-frequency fluctuations (fALFF) and regional homogeneity (ReHo) are both voxel-based functional metrics capable of estimating local spontaneous neural activities. This study aimed to investigate the local spontaneous neural activities in AS patients by utilizing the analytical approaches of fALFF and ReHo.
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