Do Demodex mites play a role in pterygium development?

Tarkowski, Witold; Moneta-Wielgoś, Joanna; Młocicki, Daniel

doi:10.1016/j.mehy.2016.09.003

Cited by 18 publications

(16 citation statements)

References 39 publications

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“… Prohic et al [ 47 ]; Moallaei et al [ 84 ] Blepharitis Chalazion Pterygium Demodex . Tarkowski et al [ 85 ] Papulopustular rosacea Increasing population of Demodex mites. Murillo et al [ 22 ] Demodex microbiota.…”

Section: Diseasesmentioning

confidence: 99%

Challenges in exploring and manipulating the human skin microbiome

Cenizo²,

et al. 2021

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The skin is the exterior interface of the human body with the environment. Despite its harsh physical landscape, the skin is colonized by diverse commensal microbes. In this review, we discuss recent insights into skin microbial populations, including their composition and role in health and disease and their modulation by intrinsic and extrinsic factors, with a focus on the pathobiological basis of skin aging. We also describe the most recent tools for investigating the skin microbiota composition and microbe-skin relationships and perspectives regarding the challenges of skin microbiome manipulation.

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Section: Diseasesmentioning

confidence: 99%

Challenges in exploring and manipulating the human skin microbiome

Cenizo²,

et al. 2021

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“…Pterygium: A significant relationship has been reported between ocular Demodex infestation and pterygium. 67 Tarkowski et al 67 hypothesised that the accumulation of biological materials by Demodex mites on the ocular surface may to lead to a chronic degeneration of conjunctival tissues, disruption of the epithelial barrier and chronic inflammation, which contribute towards pterygium formation. Alternatively, irregularities on the ocular surface due to the presence of a pterygium may provide a favourable microenvironment for Demodex and its co-pathogens.…”

Section: General Populationmentioning

confidence: 99%

Ocular Demodex: a systematic review of the clinical literature

Zhang

Müntz

Wang

et al. 2020

Ophthalmic Physiologic Optic

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Purpose: There is increasing clinical and research interest in the potential contribution of Demodex to ocular surface disease. The aim of this systematic review was to summarise and synthesise current clinical evidence relating to the aetiology, diagnosis and treatment of ocular Demodex. Recent findings: A comprehensive literature search was performed in OVID Medline, OVID Embase, and clinical trial registries, for studies published between 1990 and August 2019, examining Demodex on the ocular surface. The review included primary clinical research studies and systematic reviews of primary clinical research studies, where Demodex was considered in the context of the ocular surface and/or adnexa. Studies were categorised using the National Health and Medical Research Council evidence hierarchy. Risk of bias assessment was performed using validated tools for studies categorised as providing Level I or II evidence. A total of 87 studies were eligible for inclusion, including two systematic reviews. Most studies (60%) were observational, describing the prevalence of ocular Demodex in different clinical populations. There was a high degree of variability in the epidemiological data derived from cross-sectional aetiology studies. There was mostly consistent evidence to support an association between ocular Demodex and chronic blepharitis. Seven diagnostic test-accuracy studies were identified, which considered a range of techniques, including slit lamp examination for cylindrical eyelash collarettes and/or eyelash manipulation techniques, light microscopic evaluation of epilated eyelashes and in vivo confocal microscopy. There is currently no accepted gold-standard diagnostic method for ocular Demodex. For intervention studies, there was one systematic review, 11 published randomised trials, six trial registry entries, and nine case series. Despite a number of recent trials, the appropriate treatment regimen for ocular Demodex (including the optimal criteria and timing of an intervention) is not clearly established. Conclusions: This comprehensive narrative synthesis has captured the landscape of clinical evidence relating to the prevalence, aetiology, diagnosis and treatment of ocular Demodex. There remain opportunities to enhance understanding of its role in ocular surface disease, best diagnostic approaches and optimal treatment protocols.

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“…This ocular disease appears as a triangular shape tissue, growing near the nasal area and invading the cornea, as shown in Fig. 1 (c) [47]- [51]. The conjunctiva is extremely susceptible to damage by UV rays, because it is located at the outer lining, which protects the inner part of the eye.…”

Section: Pterygium and Its Medical Assessmentmentioning

confidence: 99%

“…Unlike pterygium, pinguecula does not spread to the corneal area. However, it can potentially develop into pterygium if the tissue continues to grow on the sclera and enter the corneal region [51]. According to Viso et al [54], this conjunctivitis tissue will lead to vision disorders that are categorised as noncancerous; it is not harmful [56] but should be of concern to prevent the disease from causing vision disturbances.…”

Section: Pterygium and Its Medical Assessmentmentioning

confidence: 99%

Automated Pterygium Detection Using Deep Neural Network

et al. 2020

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Ocular imaging has developed rapidly and plays a critical role in clinical care and ocular disease management. Development of image processing technologies pertinent to ocular diseases has paved the way for automated diagnostic systems including detection techniques using deep learning (DL) approaches. The prevalence of an abnormal tissue layer in the conjunctiva, known as pterygium eye disease, is increasing due to lack of awareness. Despite the non-cancerous/benign nature of pterygium, a clinical diagnosis from an ophthalmologist is still required to prevent the pterygium tissues from extending into the pupil, which would result in blurred vision. However, current diagnostic methods are mostly dependent on human expertise. Automated detection can potentially serve as an assistive method to reduce diagnosis time by applying a DL approach. Considering the lack of comprehensive research work on pterygium detection using DL, we propose a new architecture consisting of an improved CNN-based trained network named VggNet16-wbn that is derived from VggNet16, a pre-trained CNN algorithm. This paper presents an overview of the DL as a core approach to the transfer learning (TL) concept, as well as current efforts towards automated ocular detection approaches. A new architecture of a CNN-based trained network was proposed based on a network assessment from six CNN pre-trained networks to detect pterygium. This work consists of two main modules, namely, data acquisition and DCNN classification. The proposed trained network, VggNet16-wbn, shows the best performance with 99.22% accuracy, 98.45% sensitivity, and a perfect score on specificity and area under the curve metrics. This work has high potential for creating a pterygium screening system that can be used as a baseline for fully automated detection using a DL approach.

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Do Demodex mites play a role in pterygium development?

Cited by 18 publications

References 39 publications

Challenges in exploring and manipulating the human skin microbiome

Challenges in exploring and manipulating the human skin microbiome

Ocular Demodex: a systematic review of the clinical literature

Automated Pterygium Detection Using Deep Neural Network

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