The outcome of fluocinolone acetonide intravitreal implant is predicted by the response to dexamethasone implant in diabetic macular oedema

Background/Objectives: To investigate if the visual and anatomic response to the first dexamethasone implant (DEX) predicts the 12-month clinical outcome after shifting to fluocinolone acetonide (FAc) implant in patients with diabetic macular oedema (DMO). Methods: Retrospective cohort study including pseudophakic patients with previously treated DMO, undergone one or more DEX injections before FAc. Functional and morphologic response to DEX was defined based on the best-corrected visual acuity (BCVA) and central macular thickness (CMT) changes after the first DEX, respectively. Steroid-response was defined as intraocular pressure (IOP) elevation ≥5 mmHg or IOP > 21 mmHg after any previous DEX exposure. Pairwise comparisons for BCVA, CMT, and IOP after FAc were performed with linear mixed models and a repeated-measure design. Results: Forty-four eyes of 33 patients were included. Patients were shifted to FAc after a mean ± standard deviation of 4.6 ± 3.2 DEX injections. Overall, BCVA and CMT improved during the first 12 months after switching to FAc (p = 0.04 and p < 0.001, respectively). Only eyes with a good morphologic response to DEX had a significant CMT reduction after FAc (p < 0.001), while no significant relationship was found between BCVA improvement after DEX and after FAc. IOP elevation occurred in 9 eyes (20%) following DEX implant. These eyes carried a 20-fold increased risk of having an IOP rise after FAc (p < 0.001), with a non-linear relationship between the IOP increase after DEX and the one after FAc. Conclusion: The response to previous DEX may anticipate the morphologic response to subsequent FAc. Eyes with steroid-induced IOP elevation after DEX are at a high risk of IOP increase after FAc. The visual response after FAc was not associated with the visual response to previous steroids, indicating that FAc may have a role also in patients refractory to DEX implant. © 2021, The Author(s), under exclusive licence to The Royal College of Ophthalmologists

Alternative splicing in the ENCODE protein complement

An accurate description of current scientific developments in the field of bioinformatics and computational implementation is presented by research of the BioSapiens Network of Excellence. Bioinformatics is essential for annotating the structure and function of genes, proteins and the analysis of complete genomes and to molecular biology and biochemistry. Included is an overview of bioinformatics, the full spectrum of genome annotation approaches including; genome analysis and gene prediction, gene regulation analysis and expression, genome variation and QTL analysis, large scale protein annotation of function and structure, annotation and prediction of protein interactions, and the organization and annotation of molecular networks and biochemical pathways. Also covered is a technical framework to organize and represent genome data using the DAS technology and work in the annotation of two large genomic sets: HIV/HCV viral genomes and splicing alternatives potentially encoded in 1% of the human genome

Alternative splicing in the ENCODE protein complement

An accurate description of current scientific developments in the field of bioinformatics and computational implementation is presented by research of the BioSapiens Network of Excellence. Bioinformatics is essential for annotating the structure and function of genes, proteins and the analysis of complete genomes and to molecular biology and biochemistry. Included is an overview of bioinformatics, the full spectrum of genome annotation approaches including; genome analysis and gene prediction, gene regulation analysis and expression, genome variation and QTL analysis, large scale protein annotation of function and structure, annotation and prediction of protein interactions, and the organization and annotation of molecular networks and biochemical pathways. Also covered is a technical framework to organize and represent genome data using the DAS technology and work in the annotation of two large genomic sets: HIV/HCV viral genomes and splicing alternatives potentially encoded in 1% of the human genome