Der Effekt UV-blockierender Kontaktlinsen bei der Therapie der Keratitis superficialis chronica des Hundes

Objective Canine chronic superficial keratitis (CSK) is chronic, progressive keratopathy, which is suspected to be caused by an immune mediated response triggered by ultraviolet light exposure. The purpose of this study was to evaluate the effect of UV-blocking soft contact lenses in treatment for CSK. Methods 26 dogs (26 eyes) with CSK were treated continuously with UV-blocking contact lenses (*Acri.Pat®-UV bandage lenses) for six months. A contact lens was placed on one eye of each dog; the other eye remained without a lens as a control eye. Then, five dogs were treated further on wearing now contact lenses on either eye. Continuously, all patients were treated topically with cyclosporine A on both eyes. The contact lenses were changed every four weeks and an ophthalmic examination was performed at each appointment. Evaluation criteria included corneal alterations as pigmentation, edema, pannus and vascularisation based on digital photographs and drawings. To determine the transmittance characteristics of the contact lenses before and after use, 32 contact lenses were measured with a UV-vis-NIR spectrophotometer. Results Pigmentation increased in eyes wearing contact lenses and in control eyes over the evaluation period of six months. Corneal edema increased in the eyes wearing lenses, but remained unaffected in the control eyes. A significant difference in the incidence of pannus and the extent of corneal vascularisation could not be evaluated. Side effects were noted in six cases (corneal edema and vascularisation, conjunctivitis, blepharospasm). All new lenses studied reduced UV-radiation to a safe level, whereas used lenses did not maintain their transmittance characteristics. Conclusion Extended wear of UV-blocking contact lenses is an ineffective treatment for canine CSK and bears the risk of severe side effect

Cynomolgus monkey's choroid reference database derived from hybrid deep learning optical coherence tomography segmentation.

Cynomolgus monkeys exhibit human-like features, such as a fovea, so they are often used in non-clinical research. Nevertheless, little is known about the natural variation of the choroidal thickness in relation to origin and sex. A combination of deep learning and a deterministic computer vision algorithm was applied for automatic segmentation of foveolar optical coherence tomography images in cynomolgus monkeys. The main evaluation parameters were choroidal thickness and surface area directed from the deepest point on OCT images within the fovea, marked as the nulla with regard to sex and origin. Reference choroid landmarks were set underneath the nulla and at 500 µm intervals laterally up to a distance of 2000 µm nasally and temporally, complemented by a sub-analysis of the central bouquet of cones. 203 animals contributed 374 eyes for a reference choroid database. The overall average central choroidal thickness was 193 µm with a coefficient of variation of 7.8%, and the overall mean surface area of the central bouquet temporally was 19,335 µm2 and nasally was 19,283 µm2. The choroidal thickness of the fovea appears relatively homogeneous between the sexes and the studied origins. However, considerable natural variation has been observed, which needs to be appreciated

Uncovering of intraspecies macular heterogeneity in cynomolgus monkeys using hybrid machine learning optical coherence tomography image segmentation

The fovea is a depression in the center of the macula and is the site of the highest visual acuity. Optical coherence tomography (OCT) has contributed considerably in elucidating the pathologic changes in the fovea and is now being considered as an accompanying imaging method in drug development, such as antivascular endothelial growth factor and its safety profiling. Because animal numbers are limited in preclinical studies and automatized image evaluation tools have not yet been routinely employed, essential reference data describing the morphologic variations in macular thickness in laboratory cynomolgus monkeys are sparse to nonexistent. A hybrid machine learning algorithm was applied for automated OCT image processing and measurements of central retina thickness and surface area values. Morphological variations and the effects of sex and geographical origin were determined. Based on our findings, the fovea parameters are specific to the geographic origin. Despite morphological similarities among cynomolgus monkeys, considerable variations in the foveolar contour, even within the same species but from different geographic origins, were found. The results of the reference database show that not only the entire retinal thickness, but also the macular subfields, should be considered when designing preclinical studies and in the interpretation of foveal data

Unraveling the deep learning gearbox in optical coherence tomography image segmentation towards explainable artificial intelligence

Machine learning has greatly facilitated the analysis of medical data, while the internal operations usually remain intransparent. To better comprehend these opaque procedures, a convolutional neural network for optical coherence tomography image segmentation was enhanced with a Traceable Relevance Explainability (T-REX) technique. The proposed application was based on three components: ground truth generation by multiple graders, calculation of Hamming distances among graders and the machine learning algorithm, as well as a smart data visualization ('neural recording'). An overall average variability of 1.75% between the human graders and the algorithm was found, slightly minor to 2.02% among human graders. The ambiguity in ground truth had noteworthy impact on machine learning results, which could be visualized. The convolutional neural network balanced between graders and allowed for modifiable predictions dependent on the compartment. Using the proposed T-REX setup, machine learning processes could be rendered more transparent and understandable, possibly leading to optimized applications

Challenging a Myth and Misconception: Red-Light Vision in Rats

Due to the lack of L-cones in the rodent retina, it is generally assumed that red light is invisible to rodents. Thus, red lights and red filter foils are widely used in rodent husbandry and experimentation allowing researchers to observe animals in an environment that is thought to appear dark to the animals. To better understand red-light vision in rodents, we assessed retinal sensitivity of pigmented and albino rats to far-red light by electroretinogram. We examined the sensitivity to red light not only on the light- but also dark-adapted retina, as red observation lights in husbandry are used during the dark phase of the light cycle. Intriguingly, both rods and cones of pigmented as well as albino rats show a retinal response to red light, with a high sensitivity of the dark-adapted retina and large electroretinogram responses in the mesopic range. Our results challenge the misconception of rodents being red-light blind. Researchers and housing facilities should rethink the use of red observation lights at night

Increased 4R tau expression and behavioural changes in a novel MAPT-N296H genomic mouse model of tauopathy

The microtubule-associated protein tau is implicated in various neurodegenerative diseases including Alzheimer's disease, progressive supranuclear palsy and corticobasal degeneration, which are characterized by intracellular accumulation of hyperphosphorylated tau. Mutations in the tau gene MAPT cause frontotemporal dementia with parkinsonism linked to chromosome 17 (FTDP-17). In the human central nervous system, six tau isoforms are expressed, and imbalances in tau isoform ratios are associated with pathology. To date, few animal models of tauopathy allow for the potential influence of these protein isoforms, relying instead on cDNA-based transgene expression. Using the P1-derived artificial chromosome (PAC) technology, we created mouse lines expressing all six tau isoforms from the human MAPT locus, harbouring either the wild-type sequence or the disease-associated N296H mutation on an endogenous Mapt-/- background. Animals expressing N296H mutant tau recapitulated early key features of tauopathic disease, including a tau isoform imbalance and tau hyperphosphorylation in the absence of somatodendritic tau inclusions. Furthermore, N296H animals displayed behavioural anomalies such as hyperactivity, increased time in the open arms of the elevated plus maze and increased immobility during the tail suspension test. The mouse models described provide an excellent model to study the function of wild-type or mutant tau in a highly physiological setting

Macular thickness measurements of healthy, naïve cynomolgus monkeys assessed with spectral-domain optical coherence tomography (SD-OCT).

The purpose of this study was to measure central macular thickness in an unprecedented number of cynomolgus monkeys. Macular thickness was measured with Heidelberg spectral-domain OCT in 320 eyes of healthy and treatment-naïve cynomolgus monkeys (80 males and 80 females). The macula was successfully measured in all 320 eyes. Macular thickness was not significantly different between the sexes. The mean central macular thickness was 244 μm (+/- 21 μm). Macular thicknesses in the quadrants were 327 +/-17 μm (temporal inner), 339 +/- 17 μm (inferior inner), 341 +/- 14 μm (superior inner), 341 +/-18 μm (nasal inner), and 299 +/- 20 μm (temporal outer), 320 +/- 16 μm (superior outer), 332 +/-23 μm (inferior outer), and 337 +/-18 μm (nasal outer). Highly significant differences between the nasal and temporal quadrants were detected. This study successfully demonstrated the feasibility of retinal thickness measurements in healthy cynomolgus monkeys. The present findings indicate that the macula is thicker in cynomolgus monkeys than in humans and provide important normative data for future studies

Principal Component Analysis (PCA) plots of choroidal volumes S1 –S9.

(a) and (c) are scree plots showing the cumulative eigenvalues of the nine principal components (PCs) for right and left eyes, respectively. Eigenvalues indicate the explained variability of the respective PC. The first two PCs explain 88.1% and 88.8% of the variability in right and left eyes, respectively. (b) and (d) show projections of the data onto the first two principal components for right and left eyes, respectively.</p

Principal component analysis coefficients of the first two principal components for right and left eyes.

Principal component analysis coefficients of the first two principal components for right and left eyes.</p

Choroidal volume measurements in a right eye.

a. A machine learning algorithm was trained to detect the choroid from an obtained macula volume OCT scan (highlighted in yellow; brown = vitreous, blue = retina). For a better overview, only a single B-scan is illustrated here. Consequently, a classic algorithm automatically defined the deepest location within the foveolar depression which was marked a nulla (arrow, red spot). b. Starting from nulla, a rectangle (depicted in pink) was defined to the side with a total length of 3000 μm. c. This rectangle was rotated axially centered on nulla to segment the choroid within the OCT volume allowing measurements only the central and paracentral subfields. d. From the segmented choroid volume, choroidal sub-fields were analyzed, marked as circular zones, quadrants, and slices. (outer zones 10–13 were not investigated).</p