Noninvasive, In Vivo Assessment of Mouse Retinal Structure Using Optical Coherence Tomography

BACKGROUND: Optical coherence tomography (OCT) is a novel method of retinal in vivo imaging. In this study, we assessed the potential of OCT to yield histology-analogue sections in mouse models of retinal degeneration. METHODOLOGY/PRINCIPAL FINDINGS: We achieved to adapt a commercial 3(rd) generation OCT system to obtain and quantify high-resolution morphological sections of the mouse retina which so far required in vitro histology. OCT and histology were compared in models with developmental defects, light damage, and inherited retinal degenerations. In conditional knockout mice deficient in retinal retinoblastoma protein Rb, the gradient of Cre expression from center to periphery, leading to a gradual reduction of retinal thickness, was clearly visible and well topographically quantifiable. In Nrl knockout mice, the layer involvement in the formation of rosette-like structures was similarly clear as in histology. OCT examination of focal light damage, well demarcated by the autofluorescence pattern, revealed a practically complete loss of photoreceptors with preservation of inner retinal layers, but also more subtle changes like edema formation. In Crb1 knockout mice (a model for Leber's congenital amaurosis), retinal vessels slipping through the outer nuclear layer towards the retinal pigment epithelium (RPE) due to the lack of adhesion in the subapical region of the photoreceptor inner segments could be well identified. CONCLUSIONS/SIGNIFICANCE: We found that with the OCT we were able to detect and analyze a wide range of mouse retinal pathology, and the results compared well to histological sections. In addition, the technique allows to follow individual animals over time, thereby reducing the numbers of study animals needed, and to assess dynamic processes like edema formation. The results clearly indicate that OCT has the potential to revolutionize the future design of respective short- and long-term studies, as well as the preclinical assessment of therapeutic strategies

Mutation Rate Switch inside Eurasian Mitochondrial Haplogroups: Impact of Selection and Consequences for Dating Settlement in Europe

R-lineage mitochondrial DNA represents over 90% of the European population and is significantly present all around the planet (North Africa, Asia, Oceania, and America). This lineage played a major role in migration “out of Africa” and colonization in Europe. In order to determine an accurate dating of the R lineage and its sublineages, we analyzed 1173 individuals and complete mtDNA sequences from Mitomap. This analysis revealed a new coalescence age for R at 54.500 years, as well as several limitations of standard dating methods, likely to lead to false interpretations. These findings highlight the association of a striking under-accumulation of synonymous mutations, an over-accumulation of non-synonymous mutations, and the phenotypic effect on haplogroup J. Consequently, haplogroup J is apparently not a Neolithic group but an older haplogroup (Paleolithic) that was subjected to an underestimated selective force. These findings also indicated an under-accumulation of synonymous and non-synonymous mutations localized on coding and non-coding (HVS1) sequences for haplogroup R0, which contains the major haplogroups H and V. These new dates are likely to impact the present colonization model for Europe and confirm the late glacial resettlement scenario

Machine learning applications in detection and diagnosis of urology cancers: a systematic literature review

Deep learning integration in cancer diagnosis enhances accuracy and diagnosis speed which helps clinical decision-making and improves health outcomes. Despite all these benefits in cancer diagnosis, the present AI models in urology cancer diagnosis have not been sufficiently reviewed systematically. This paper reviews the artificial intelligence approaches used in cancer diagnosis, prediction, and treatment of urology cancer. AI models and their applications in urology subspecialties are evaluated and discussed. The Scopus, Microsoft Academic and PubMed/MEDLINE databases were searched in November 2022 using the terms “artificial intelligence”, “neural network”, “machine learning,” or “deep learning” combined with the phrase “urology cancers”. The search was limited to publications published within the previous 20 years to identify cutting-edge deep-learning applications published in English. Irrelevant review articles and publications were eliminated. The included research involves two kinds of research analysis: quantitative and qualitative. 48 articles were included in this survey. 25 studies proposed several approaches for prostate cancers, while 15 were for bladder cancers. 8 studies discussed renal cell carcinoma and kidney cancer. The models presented to detect urology cancers have achieved high detection accuracy (77–95%). Deep learning approaches that use convolutional neural networks have achieved the highest accuracy among other techniques. Although it is still progressing, the development of AI models for urology cancer detection, prediction, and therapy has shown significant promise. Additional research is required to employ more extensive, higher-quality, and more recent datasets to the clinical performance of the proposed AI models in urology cancer applications

Future Holiday Climate Index (HCI) Performance of Urban and Beach Destinations in the Mediterranean

Tourism is a major socioeconomic contributor to established and emerging destinations in the Mediterranean region. Recent studies introducing the Holiday Climate Index (HCI) highlight the significance of climate as a factor in sustaining the competitiveness of coastal and urban destinations. The aim of this study is to assess the future HCI performance of urban and beach destinations in the greater Mediterranean region. For this purpose, HCI scores for the reference (1971–2000) and future (2021–2050, 2070–2099) periods were computed with the use of two latest greenhouse gas concentration trajectories, RCP 4.5 and 8.5, based on the Middle East North Africa (MENA) Coordinated Regional Downscaling Experiment (CORDEX) domain and data. The outputs were adjusted to a 500 m resolution via the use of lapse rate corrections that extrapolate the climate model topography against a resampled digital elevation model. All periodic results were seasonally aggregated and visualized on a (web) geographical information system (GIS). The web version of the GIS also allowed for a basic climate service where any user can search her/his place of interest overlaid with index ratings. Exposure levels are revealed at the macro scale while sensitivity is discussed through a validation of the climatic outputs against visitation data for one of Mediterranean's leading destinations, Antalya

Rapid cohort generation and analysis of disease spectrum of large animal model of cone dystrophy.

Large animal models are an important resource for the understanding of human disease and for evaluating the applicability of new therapies to human patients. For many diseases, such as cone dystrophy, research effort is hampered by the lack of such models. Lentiviral transgenesis is a methodology broadly applicable to animals from many different species. When conjugated to the expression of a dominant mutant protein, this technology offers an attractive approach to generate new large animal models in a heterogeneous background. We adopted this strategy to mimic the phenotype diversity encounter in humans and generate a cohort of pigs for cone dystrophy by expressing a dominant mutant allele of the guanylate cyclase 2D (GUCY2D) gene. Sixty percent of the piglets were transgenic, with mutant GUCY2D mRNA detected in the retina of all animals tested. Functional impairment of vision was observed among the transgenic pigs at 3 months of age, with a follow-up at 1 year indicating a subsequent slower progression of phenotype. Abnormal retina morphology, notably among the cone photoreceptor cell population, was observed exclusively amongst the transgenic animals. Of particular note, these transgenic animals were characterized by a range in the severity of the phenotype, reflecting the human clinical situation. We demonstrate that a transgenic approach using lentiviral vectors offers a powerful tool for large animal model development. Not only is the efficiency of transgenesis higher than conventional transgenic methodology but this technique also produces a heterogeneous cohort of transgenic animals that mimics the genetic variation encountered in human patients

Earth System Model Evaluation Tool (ESMValTool) v2.0-diagnostics for extreme events, regional and impact evaluation, and analysis of Earth system models in CMIP

This paper complements a series of now four publications that document the release of the Earth System Model Evaluation Tool (ESMValTool) v2.0. It describes new diagnostics on the hydrological cycle, extreme events, impact assessment, regional evaluations, and ensemble member selection. The diagnostics are developed by a large community of scientists aiming to facilitate the evaluation and comparison of Earth system models (ESMs) which are participating in the Coupled Model Intercomparison Project (CMIP). The second release of this tool aims to support the evaluation of ESMs participating in CMIP Phase 6 (CMIP6). Furthermore, datasets from other models and observations can be analysed. The diagnostics for the hydrological cycle include several precipitation and drought indices, as well as hydroclimatic intensity and indices from the Expert Team on Climate Change Detection and Indices (ETCCDI). The latter are also used for identification of extreme events, for impact assessment, and to project and characterize the risks and impacts of climate change for natural and socio-economic systems. Further impact assessment diagnostics are included to compute daily temperature ranges and capacity factors for wind and solar energy generation. Regional scales can be analysed with new diagnostics implemented for selected regions and stochastic downscaling. ESMValTool v2.0 also includes diagnostics to analyse large multi-model ensembles including grouping and selecting ensemble members by user-specified criteria. Here, we present examples for their capabilities based on the well-established CMIP Phase 5 (CMIP5) dataset

Topographic analysis of retinal thickness in an organ-specific model of retinoblastoma protein (<i>Rb</i>) deficiency.

<p>Thickness variations (center vs. periphery) were caused by imperfections of the Cre-lox system (see text), leading to differences in developmental apoptosis. A) Histological section across the central retina showing the smooth transition between centrally normal and peripherally reduced thickness. B) OCT section of the same region, the retinal thickness correlating well with the histomorphological data. C) Assessment of the gradual changes of retinal thickness from center to (mid)periphery based on 5 manually placed OCT slices. Left: SLO image of the fundus region with the position of the slices superimposed. Right: OCT slices at the positions indicated, ordered from center to periphery. D) Topography of retinal thickness calculated from 92 equidistant OCT slices (“volume scan” data). The color scale values are in µm.</p

Capability of the OCT to detect and capture the nature of lesions.

<p>A)–D) Site of neovascularization in a Crumbs 1 (<i>Crb1</i>) knockout mouse. A) SLO fluorescence angiographic (FLA) image of a retinal neovascular site (arrow) in a representative <i>Crb1</i> knockout mouse. B) Detail of g) illustrating the traction the aberrant vessel applies to the neighboring capillaries. C) Representative OCT slice depicting enlarged aberrant retinal vessels (black arrow) as well as choroidal vascular changes (white arrow) at the same position, implicating a connection between both vascular beds. D) Histological section of the above neovascular site for comparison. The black arrow points to aberrant retinal vessels, and the white arrow to choroidal changes.</p

Capability of the OCT to detect and capture the nature of lesions.

<p>A)–F) Multiple retinal rosette formation in the neural retinal leucine zipper (<i>Nrl</i>) knockout mouse. A) SLO surface image (514 nm) in which the retinal rosettes (arrow) show as whitish dots. B) SLO autofluorescence image indicating that the rosettes contain fluorescent material. C) Representative OCT slice of a <i>Nrl</i> knockout mouse revealing details of the nature of the rosettes (arrow) and their depth localization. D) Comparison of the OCT representation of <i>Nrl</i> rosettes with histology (different individual animal). E, F) Detail illustrating how well retinal structures in OCT and histology correlate.</p