Heritability of distichiasis in Havanese dogs in Norway

Background Distichiasis is a presumed inherited eyelid disease, characterized by misplaced eyelashes. The effect on eye health and animal welfare varies between individuals; most mild cases show no clinical signs, but some affected animals develop painful corneal disease. In this study, we investigated the prevalence and heritability of distichiasis in the Norwegian population of Havanese dogs. Results A total of 1156 Havanese were included in the study. Out of these, 168 were affected with distichiasis, making the prevalence in our sample 14.5% (95% CI 12.5–16.6%). There was no sex predisposition. Most affected individuals were graded “mildly affected”. The estimates generally showed high heritabilities, which varied between 0.276 (linear model) and 0.720 (Bayesian threshold model). The linear estimates, after conversion to the underlying scale (h2l = 0.664–0.674), corresponds well to the results of the Bayesian models. Conclusions The estimated heritability of distichiasis in Havanese is high and the prevalence is moderate. The high heritability indicate that a significant selection response could be obtained by simple mass selection. To secure good animal welfare, it’s important to control the number of affected individuals and especially the severely affected.

Population-based study on the prevalence, clinical characteristics and vision-related quality of life in patients with corneal opacity resulting from infectious keratitis: results from the Corneal Opacity Rural Epidemiological study

AimTo estimate prevalence and characterise clinical features and vision-related quality of life (VR-QoL) of corneal opacities (COs) resulting from infectious keratitis in a rural North Indian population.MethodsThe Corneal Opacity Rural Epidemiological study was a cross-sectional study conducted in 25 randomly selected clusters of rural Gurgaon, Haryana, India to determine prevalence of corneal disease across all age groups. During house-to-house visits, sociodemographic details, presence, type and clinical characteristics of corneal disease, laterality and resultant visual impairment (VI) was noted. Subgroup analysis of data was performed to understand the prevalence, clinical characteristics, VR-QoL in patients with CO due to infectious keratitis. VR-QoL scores were compared with healthy controls.ResultsOverall, 65 of 12 113 participants had evidence of infectious keratitis-related CO with a mean age of 63.3 (±14.7 SD) years. Prevalence of infectious keratitis-related CO, including both bilateral (12/65) and unilateral (53/65) cases was 0.54% (95% CI 0.41 to 0.66) seen in a total of 77 eyes of 65 participants. Mean visual acuity was 1.18±0.80 with 30/77 (38.9%) eyes having a presenting visual acuity <3/60. Most of the CO due to infectious keratitis was <3 mm in size (61.03%; 47/77), nebular (42.85%; 33/77) and central (49.35%; 38/77) in location. These participants had significantly higher VR-QoL scores and hence poorer VR-QoL across all three domains of vision function (scores of 28 vs 22, 7.5 vs 5 and 15.5 vs 9, respectively; p<0.0001) when compared with healthy controls.ConclusionThe data from this study give an insight into the burden and clinical characteristics of COs resulting from infectious keratitis. VR-QoL is significantly impaired in patients with CO resulting from infectious keratitis, both in bilateral and unilateral cases.

Corneal neurotisation for neurotrophic keratopathy with a sural nerve autograft: a case report

Neurotrophic keratopathy is a corneal disease characterised by reduced corneal sensation. Corneal neurotization is the transfer of healthy donor nerve tissue to the cornea to restore sensation. An 11-year-old male presented with reduced Mackie Stage 1 neurotrophic keratopathy from de-bulking of a cerebellopontine angle arachnoid cyst. He underwent minimally invasive indirect corneal neurotization with a sural nerve autograft to ipsilateral supratrochlear nerve and cornea. Close and objective post-operative monitoring of donor sites, the cornea, visual acuity, and tear production clearly demonstrate the efficacy of this technique, and the timeline of clinical improvement.

Comparative Analysis of Deep Learning Methods for Detection of Keratoconus

Keratoconus eye disease is not an inflammatory corneal disease that is caused by progress in thinning of the cornea, scarring, and deformation in the shape of the cornea. In India, there is a significant increase in the number of cases of keratoconus, and several research centers have been paying attention to this disease in recent years. In this situation, there is an immediate need for tools that simplify both diagnosis and treatment[1]. The algorithm developed can decide whether the eye is a normal eye or keratoconus eye with stages. The K-net model analyzes the pentagram images of the eye using a convolutional neural network(CNN) a deep learning model and pre-trained ResNet-50 and InceptionV3 pre-trained models and does the comparative analysis of the accuracies of these models. The results show that the Keratoconus Detection algorithm leads to a good job, with a 93.75 percent accuracy on the data test collection. Keratoconus Detection model is a program that can help ophthalmologists test their patients faster, therefore reducing diagnostic errors and facilitating treatment.

Eye Banks: Future Perspectives

Technological progress and societal change are transforming medicine, and cornea banks are no exception. New infectiological factors, statutory requirements, management concepts, globalisation and digitalisation are also influencing how such facilities will operate in the future. The goal of providing high quality material to patients with corneal disease remains unaltered. The present article seeks to shed light on the type of material this will involve and under what circumstances it is to be obtained.