The innate immune system in diabetic retinopathy

Pan, Warren; Lin, Feng; Fort, Patrice E.

doi:10.1016/j.preteyeres.2021.100940

Cited by 54 publications

(25 citation statements)

References 307 publications

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“…Glucose levels in the posterior region of the vitreous humor have been shown to be higher than the central or anterior regions of the vitreous humor in diabetics [44], and may be reflective of the metabolic process at the retina level. However, even prior to the vascular findings of microaneurysms and other microvascular changes found in clinical DR, pre-clinical neurodegenerative findings can be found in DR and are thought to be induced through innate immunogenic and pro-inflammatory responses [49]. The data on the vitreous in nonproliferative diabetic retinopathy (NPDR) cases are very limited because of the difficulty of sampling in those patients who do not need vitrectomy.…”

Section: The Glycemic Statementioning

confidence: 99%

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The Vitreous Ecosystem in Diabetic Retinopathy: Insight into the Patho-Mechanisms of Disease

Iyer

Lagrew

Tillit

et al. 2021

IJMS

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Diabetic retinopathy is one of the leading causes of blindness in the world with the incidence of disease ever-increasing worldwide. The vitreous humor represents an extensive and complex interactive arena for cytokines in the diabetic eye. In recent decades, there has been significant progress in understanding this environment and its implications in disease pathophysiology. In this review, we investigate the vitreous ecosystem in diabetic retinopathy at the molecular level. Areas of concentration include: the current level of knowledge of growth factors, cytokine and chemokine mediators, and lipid-derived metabolites in the vitreous. We discuss the molecular patho-mechanisms of diabetic retinopathy based upon current vitreous research.

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Section: The Glycemic Statementioning

confidence: 99%

“…Even prior to the clinical evidence of DR, the pro-inflammatory and neuro-degenerative pathways that start damage early in the diabetic retina may be immune-mediated and involve the complement system [49,56]. The complement system consists of three major pathways: classic, alternative, and lectin [177].…”

Section: Complementmentioning

confidence: 99%

The Vitreous Ecosystem in Diabetic Retinopathy: Insight into the Patho-Mechanisms of Disease

Iyer

Lagrew

Tillit

et al. 2021

IJMS

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“… 1 PDR has classically been known as a microvascular complication of diabetes and is characterized by vascular abnormalities. 2 However, recent discoveries have indicated involvement of the immune system, particularly the complement system, in maintaining retinal integrity, disease pathogenesis, and severity. 3 , 4 In line with these findings, a number of inflammatory cytokines and chemokines have been reported to be elevated in ocular tissues of both patients with PDR and animal models.…”

mentioning

confidence: 99%

Bulk Gene Expression Deconvolution Reveals Infiltration of M2 Macrophages in Retinal Neovascularization

Wang

Kumar

Liu

2021

Invest. Ophthalmol. Vis. Sci.

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“…Modern healthcare methods actively use retinal fundus images for the diagnosis [ 26 , 27 , 28 , 29 ]. In this section, we critically review the prominent work on hemorrhage detection from the retinal fundus images.…”

Section: Related Workmentioning

confidence: 99%

Hemorrhage Detection Based on 3D CNN Deep Learning Framework and Feature Fusion for Evaluating Retinal Abnormality in Diabetic Patients

Maqsood

Damaševičius

Maskeliūnas

2021

Sensors

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Diabetic retinopathy (DR) is the main cause of blindness in diabetic patients. Early and accurate diagnosis can improve the analysis and prognosis of the disease. One of the earliest symptoms of DR are the hemorrhages in the retina. Therefore, we propose a new method for accurate hemorrhage detection from the retinal fundus images. First, the proposed method uses the modified contrast enhancement method to improve the edge details from the input retinal fundus images. In the second stage, a new convolutional neural network (CNN) architecture is proposed to detect hemorrhages. A modified pre-trained CNN model is used to extract features from the detected hemorrhages. In the third stage, all extracted feature vectors are fused using the convolutional sparse image decomposition method, and finally, the best features are selected by using the multi-logistic regression controlled entropy variance approach. The proposed method is evaluated on 1509 images from HRF, DRIVE, STARE, MESSIDOR, DIARETDB0, and DIARETDB1 databases and achieves the average accuracy of 97.71%, which is superior to the previous works. Moreover, the proposed hemorrhage detection system attains better performance, in terms of visual quality and quantitative analysis with high accuracy, in comparison with the state-of-the-art methods.

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The innate immune system in diabetic retinopathy

Cited by 54 publications

References 307 publications

The Vitreous Ecosystem in Diabetic Retinopathy: Insight into the Patho-Mechanisms of Disease

The Vitreous Ecosystem in Diabetic Retinopathy: Insight into the Patho-Mechanisms of Disease

Bulk Gene Expression Deconvolution Reveals Infiltration of M2 Macrophages in Retinal Neovascularization

Hemorrhage Detection Based on 3D CNN Deep Learning Framework and Feature Fusion for Evaluating Retinal Abnormality in Diabetic Patients

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