Progression of Retinopathy Secondary to Maternally Inherited Diabetes and Deafness – Evaluation of Predicting Parameters

PURPOSE: To investigate the prognostic value of demographic, functional, and imaging parameters on retinal pigment epithelium (RPE) atrophy progression secondary to Maternally Inherited Diabetes and Deafness (MIDD) and to evaluate the application of these factors in clinical trial design. DESIGN: Retrospective observational case series. METHODS: Thirty-five eyes of 20 patients (age range, 24.9-75.9 years) with genetically proven MIDD and demarcated RPE atrophy on serial fundus autofluorescence (AF) images were included. Lesion size and shape-descriptive parameters were longitudinally determined by two independent readers. A linear mixed effect model was used to predict the lesion enlargement rate based on baseline variables. Sample size calculations were performed to model the power in a simulated interventional study. RESULTS: The mean follow-up time was 4.27 years. The mean progression rate of RPE atrophy was 2.33 mm2/year revealing a dependence on baseline lesion size (+0.04 [0.02-0.07] mm2/year/mm2, p<0.001), which was absent after square root transformation. The fovea was preserved in the majority of patients during the observation time. In the case of foveal involvement, the loss of visual acuity lagged behind central RPE atrophy in AF images. Sex, age, and number of atrophic foci predicted future progression rates with a cross-validated mean absolute error of 0.13 mm/year and to reduce the required sample size for simulated interventional trials. CONCLUSIONS: Progressive RPE atrophy could be traced in all eyes using AF imaging. Shape-descriptive factors and patients' baseline characteristics had significant prognostic value, guiding appropriate subject selection and sample size in future interventional trial design

Foveal structure and visual function in nanophthalmos and posterior microphthalmos

Background/aims: The reason for visual impairment in patients with nanophthalmos and posterior microphthalmos is not completely understood. Therefore, this study aims to investigate foveal structure, and the impact of demographic, clinical and imaging parameters on best-corrected visual acuity (BCVA) in these conditions. Methods: Sixty-two eyes of 33 patients with nanophthalmos (n=40) or posterior microphthalmos (n=22), and 114 eyes of healthy controls with high-resolution retinal imaging including spectral-domain or swept-source optical coherence tomography images were included in this cross-sectional case-control study. Foveal retinal layer thickness was determined by two independent readers. A mixed-effect model was used to perform structure-function correlations and predict the BCVA based on subject-specific variables. Results: Most patients (28/33) had altered foveal structure associated with loss of foveal avascular zone and impaired BCVA. However, widening of outer nuclear layer, lengthening of photoreceptor outer segments, normal distribution of macular pigment and presence of Henle fibres were consistently found. Apart from the presence of choroidal effusion, which had significant impact on BCVA, the features age, refractive error, axial length and retinal layer thickness at the foveal centre explained 61.7% of the variability of BCVA. Conclusion: This study demonstrates that choroidal effusion, age, refractive error, axial length and retinal layer thickness are responsible for the majority of interindividual variability of BCVA as well as the morphological foveal heterogeneity in patients with nanophthalmos or posterior microphthalmos. This might give further insights into the physiology of foveal development and the process of emmetropisation, and support clinicians in the assessment of these disease entities

Gravitational physics with antimatter

The production of low-energy antimatter provides unique opportunities to search for new physics in an unexplored regime. Testing gravitational interactions with antimatter is one such opportunity. Here a scenario based on Lorentz and CPT violation in the Standard- Model Extension is considered in which anomalous gravitational effects in antimatter could arise.Comment: 5 pages, presented at the International Conference on Exotic Atoms (EXA 2008) and the 9th International Conference on Low Energy Antiproton Physics (LEAP 2008), Vienna, Austria, September 200

Immunocytochemical determination of the subcellular distribution of ascorbate in plants

Ascorbate is an important antioxidant in plants and fulfills many functions related to plant defense, redox signaling and modulation of gene expression. We have analyzed the subcellular distribution of reduced and oxidized ascorbate in leaf cells of Arabidopsis thaliana and Nicotiana tabacum by high-resolution immuno electron microscopy. The accuracy and specificity of the applied method is supported by several observations. First, preadsorption of the ascorbate antisera with ascorbic acid or dehydroascorbic acid resulted in the reduction of the labeling to background levels. Second, the overall labeling density was reduced between 50 and 61% in the ascorbate-deficient Arabidopsis mutants vtc1-2 and vtc2-1, which correlated well with biochemical measurements. The highest ascorbate-specific labeling was detected in nuclei and the cytosol whereas the lowest levels were found in vacuoles. Intermediate labeling was observed in chloroplasts, mitochondria and peroxisomes. This method was used to determine the subcellular ascorbate distribution in leaf cells of plants exposed to high light intensity, a stress factor that is well known to cause an increase in cellular ascorbate concentration. High light intensities resulted in a strong increase in overall labeling density. Interestingly, the strongest compartment-specific increase was found in vacuoles (fourfold) and in plastids (twofold). Ascorbate-specific labeling was restricted to the matrix of mitochondria and to the stroma of chloroplasts in control plants but was also detected in the lumen of thylakoids after high light exposure. In summary, this study reveals an improved insight into the subcellular distribution of ascorbate in plants and the method can now be applied to determine compartment-specific changes in ascorbate in response to various stress situations

Susceptibility to tuberculosis is associated with variants in the ASAP1 gene encoding a regulator of dendritic cell migration

Human genetic factors predispose to tuberculosis (TB). We studied 7.6 million genetic variants in 5,530 people with pulmonary TB and in 5,607 healthy controls. In the combined analysis of these subjects and the follow-up cohort (15,087 TB patients and controls altogether), we found an association between TB and variants located in introns of the ASAP1 gene on chromosome 8q24 (P = 2.6 × 10−11 for rs4733781; P = 1.0 × 10−10 for rs10956514). Dendritic cells (DCs) showed high ASAP1 expression that was reduced after Mycobacterium tuberculosis infection, and rs10956514 was associated with the level of reduction of ASAP1 expression. The ASAP1 protein is involved in actin and membrane remodeling and has been associated with podosomes. The ASAP1-depleted DCs showed impaired matrix degradation and migration. Therefore, genetically determined excessive reduction of ASAP1 expression in M. tuberculosis–infected DCs may lead to their impaired migration, suggesting a potential mechanism of predisposition to TB

Genetic noise control via protein oligomerization

Gene expression in a cell entails random reaction events occurring over disparate time scales. Thus, molecular noise that often results in phenotypic and population-dynamic consequences sets a fundamental limit to biochemical signaling. While there have been numerous studies correlating the architecture of cellular reaction networks with noise tolerance, only a limited effort has been made to understand the dynamic role of protein-protein interactions. Here we have developed a fully stochastic model for the positive feedback control of a single gene, as well as a pair of genes (toggle switch), integrating quantitative results from previous in vivo and in vitro studies. We find that the overall noise-level is reduced and the frequency content of the noise is dramatically shifted to the physiologically irrelevant high-frequency regime in the presence of protein dimerization. This is independent of the choice of monomer or dimer as transcription factor and persists throughout the multiple model topologies considered. For the toggle switch, we additionally find that the presence of a protein dimer, either homodimer or heterodimer, may significantly reduce its random switching rate. Hence, the dimer promotes the robust function of bistable switches by preventing the uninduced (induced) state from randomly being induced (uninduced). The specific binding between regulatory proteins provides a buffer that may prevent the propagation of fluctuations in genetic activity. The capacity of the buffer is a non-monotonic function of association-dissociation rates. Since the protein oligomerization per se does not require extra protein components to be expressed, it provides a basis for the rapid control of intrinsic or extrinsic noise

Quantification of key retinal features in early and late age-related macular degeneration using deep learning

PURPOSE: To develop and validate a deep learning model for segmentation of 13 features associated with neovascular and atrophic age-related macular degeneration (AMD). DESIGN: Development and validation of a deep-learning model for feature segmentation METHODS: Data for model development were obtained from 307 optical coherence tomography volumes. Eight experienced graders manually delineated all abnormalities in 2,712 B-scans. A deep neural network was trained with this data to perform voxel-level segmentation of the 13 most common abnormalities (features). For evaluation, 112 B-scans from 112 patients with a diagnosis of neovascular AMD were annotated by four independent observers. Main outcome measures were Dice score, intra-class correlation coefficient (ICC), and free-response receiver operating characteristic (FROC) curve. RESULTS: On 11 of the 13 features, the model obtained a mean Dice score of 0.63 ± 0.15, compared to 0.61 ± 0.17 for the observers. The mean ICC for the model was 0.66 ± 0.22, compared to 0.62 ± 0.21 for the observers. Two features were not evaluated quantitatively due to lack of data. FROC analysis demonstrated that the model scored similar or higher sensitivity per false positives compared to the observers. CONCLUSIONS: The quality of the automatic segmentation matches that of experienced graders for most features, exceeding human performance for some features. The quantified parameters provided by the model can be used in the current clinical routine and open possibilities for further research into treatment response outside clinical trials