Retinopathy of prematurity: Causes, prevention and treatment

Advances in neonatal intensive care have improved survival rates in extremely premature an infant, which has led to an increase of Retinopathy of Prematurity (ROP) in the developed world. Left untreated, infants are at risk of developing strabismus, myopia, vitreous haemorrhage, vitreo-retinal fibrosis, retinal detachment, secondary angle closure glaucoma and ultimately complete loss of vision. The improvements in the understanding and treatment of ROP have been supported by seminal research, and its complexity is still being explored. However the importance of early screening and treatment is essential in the prevention and treatment of this disease. The following paper will examine the causes and treatments of ROP, as well as implications for future neonatal practice.

Survival or death: a dual role of autophagy in stress-induced pericyte loss in diabetic retinopathy

Aims/hypothesis
Intra-retinal extravasation and modification of LDL have been implicated in diabetic retinopathy: autophagy may mediate these effects.
Methods
Immunohistochemistry was used to detect autophagy marker LC3B in human and murine diabetic and non-diabetic retinas. Cultured human retinal capillary pericytes (HRCPs) were treated with in vitro-modified heavily-oxidised glycated LDL (HOG-LDL) vs native LDL (N-LDL) with or without autophagy modulators: green fluorescent protein–LC3 transfection; small interfering RNAs against Beclin-1, c-Jun NH(2)-terminal kinase (JNK) and C/EBP-homologous protein (CHOP); autophagy inhibitor 3-MA (5 mmol/l) and/or caspase inhibitor Z-VAD-fmk (100 μmol/l). Autophagy, cell viability, oxidative stress, endoplasmic reticulum stress, JNK activation, apoptosis and CHOP expression were assessed by western blots, CCK-8 assay and TUNEL assay. Finally, HOG-LDL vs N-LDL were injected intravitreally to STZ-induced diabetic vs control rats (yielding 50 and 200 mg protein/l intravitreal concentration) and, after 7 days, retinas were analysed for ER stress, autophagy and apoptosis.
Results
Intra-retinal autophagy (LC3B staining) was increased in diabetic vs non-diabetic humans and mice. In HRCPs, 50 mg/l HOG-LDL elicited autophagy without altering cell viability, and inhibition of autophagy decreased survival. At 100–200 mg/l, HOG-LDL caused significant cell death, and inhibition of either autophagy or apoptosis improved survival. Further, 25–200 mg/l HOG-LDL dose-dependently induced oxidative and ER stress. JNK activation was implicated in autophagy but not in apoptosis. In diabetic rat retina, 50 mg/l intravitreal HOG-LDL elicited autophagy and ER stress but not apoptosis; 200 mg/l elicited greater ER stress and apoptosis.
Conclusions
Autophagy has a dual role in diabetic retinopathy: under mild stress (50 mg/l HOG-LDL) it is protective; under more severe stress (200 mg/l HOG-LDL) it promotes cell death.

Posterior Probability Modeling and Image Classification for Archaeological Site Prospection: Building a Survey Efficacy Model for Identifying Neolithic Felsite Workshops in the Shetland Islands

The application of custom classification techniques and posterior probability modeling (PPM) using Worldview-2 multispectral imagery to archaeological field survey is presented in this paper. Research is focused on the identification of Neolithic felsite stone tool workshops in the North Mavine region of the Shetland Islands in Northern Scotland. Sample data from known workshops surveyed using differential GPS are used alongside known non-sites to train a linear discriminant analysis (LDA) classifier based on a combination of datasets including Worldview-2 bands, band difference ratios (BDR) and topographical derivatives. Principal components analysis is further used to test and reduce dimensionality caused by redundant datasets. Probability models were generated by LDA using principal components and tested with sites identified through geological field survey. Testing shows the prospective ability of this technique and significance between 0.05 and 0.01, and gain statistics between 0.90 and 0.94, higher than those obtained using maximum likelihood and random forest classifiers. Results suggest that this approach is best suited to relatively homogenous site types, and performs better with correlated data sources. Finally, by combining posterior probability models and least-cost analysis, a survey least-cost efficacy model is generated showing the utility of such approaches to archaeological field survey.