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IL-10 and IL-6/IL-10 as predictive biomarkers for treatment response in non-infectious uveitis
(Frontiers Media SA, 2025-05-13)
Rodrigo A. Valenzuela
;
Fabian Vega-Tapia
;
Nathaly Elizalde
;
Ivan Flores
;
Felipe M. Rojas
Uveitis, a group of heterogeneous diseases causing ocular inflammation, is a major contributor to vision loss globally. While systemic corticosteroids (CS) are the mainstay treatment, identifying CS-refractory patients remains a significant challenge. This study aimed to explore cytokine expression and Glucocorticoid Receptor (GR) levels as biomarkers for the early detection of CS-refractory cases in non-infectious uveitis. We assayed blood samples from 19 patients with non-infectious uveitis, for the expression of IL-6, IL-17A, TNF-α, IL-10 and GRα. The cohort included 11 refractory and 8 sensitive patients, categorized based on their clinical response to corticosteroids (prednisone 1 mg/kg/day). Blood draws were conducted at three time points (at baseline, day 7- and day 14 after CS initiation), and peripheral blood mononuclear cells (PBMCs) were isolated to measure cytokine and GRα transcript levels via real-time PCR. The expression levels of GRα and cytokines IL-6, IL-17A and TNF-α did not show significant changes between CS-sensitive and CS-refractory patients on the different days of treatment. However, IL-10 expression levels as the day14-to-day7 ratio were significantly higher in patients sensitive to CS therapy. A higher day14-to-day7 ratio was also found for the IL-6/IL-10, IL-17A/IL-10 and GRα/IL-10 ratios. ROC curve analysis demonstrated a robust predictive performance of IL-10 mRNA expression and the IL-6/IL-10 ratio for identifying CS-refractory patients. In conclusion, the expression of IL-10 and the IL-6/IL-10 ratio hold promise as early predictive biomarkers for CS treatment refractoriness in patients with non-infectious uveitis. These findings offer valuable insights into personalized treatment strategies, potentially leading to improved clinical outcomes.
Scopus© Citations 6 1
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Interpretable multimodal classification for age-related macular degeneration diagnosis
(2024)
Carla Vairetti
;
Sebastián Maldonado
;
Loreto Cuitino
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URZUA SALINAS, CRISTHIAN
;
Xu Yanwu
<jats:p>Explainable Artificial Intelligence (XAI) is an emerging machine learning field that has been successful in medical image analysis. Interpretable approaches are able to “unbox” the black-box decisions made by AI systems, aiding medical doctors to justify their diagnostics better. In this paper, we analyze the performance of three different XAI strategies for medical image analysis in ophthalmology. We consider a multimodal deep learning model that combines optical coherence tomography (OCT) and infrared reflectance (IR) imaging for the diagnosis of age-related macular degeneration (AMD). The classification model is able to achieve an accuracy of 0.94, performing better than other unimodal alternatives. We analyze the XAI methods in terms of their ability to identify retinal damage and ease of interpretation, concluding that grad-CAM and guided grad-CAM can be combined to have both a coarse visual justification and a fine-grained analysis of the retinal layers. We provide important insights and recommendations for practitioners on how to design automated and explainable screening tests based on the combination of two image sources.</jats:p>
Scopus© Citations 1
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Vogt-Koyanagi-Harada disease: the step-by-step approach to a better understanding of clinicopathology, immunopathology, diagnosis, and management: a brief review
(2022)
Cristhian A. Urzua
;
Carl P. Herbort
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Masaru Takeuchi
;
Ariel Schlaen
;
Luz E. Concha-del-Rio
<jats:title>Abstract</jats:title><jats:sec> <jats:title>Background</jats:title> <jats:p>Appraisals of Vogt-Koyanagi-Harada disease (VKH) have become progressively more complete, since its first description in 1906. The availability of new investigational methods has improved our knowledge of the immunopathology, clinicopathology, diagnosis, and management of VKH disease. This review aimed to describe some of the steps that led to better characterization of VKH as a clinical entity.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>We searched on PubMed for articles that described the history of VKH disease and analyzed the progress in disease appraisal with new investigational and imaging methods. In particular, we searched for articles that investigated the clinicopathology, diagnosis, and management of VKH.</jats:p> </jats:sec><jats:sec> <jats:title>Findings</jats:title> <jats:p>The following developments were considered essential for improving the appraisal and understanding of VKH: (1) the history of the disease, (2) immunopathological mechanisms, (3) clinicopathology, (4) the importance of distinguishing initial-onset from chronic disease, (5) relevant imaging modalities, among which indocyanine green angiography is crucial, (6) diagnostic criteria that facilitate early diagnosis, and (7) the need for early, prolonged, aggressive treatment that combines steroidal and non-steroidal immunosuppression.</jats:p> </jats:sec><jats:sec> <jats:title>Conclusion</jats:title> <jats:p>Based on these findings, the definition of VKH has improved. VKH disease starts in the choroidal stroma and later involves other structures when it is not diagnosed and treated early. Indocyanine green angiography and enhanced depth imaging optical coherence tomography facilitate early diagnosis and precise monitoring of choroidal inflammation. ICGA is clearly the gold standard for appraisals and follow-ups in VKH disease, however EDI-OCT should be especially considered in those areas where ICGA is not fully available. These modalities have contributed substantially to a “cure” for VKH, when treatment is introduced within the therapeutic window of opportunity.</jats:p> </jats:sec>
Scopus© Citations 25 1
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Definition of Uveitis Refractory to Treatment: A Systematic Review in the Absence of a Consensus
(2020)
Rodrigo A. Valenzuela
;
Iván Flores
;
Myriam Pujol
;
Carolina Llanos
;
Ester Carreño
3Scopus© Citations 10

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