Retinal differentiation of human bone marrow-derived stem cells by co-culture with retinal pigment epithelium in vitro.

The goal of this study was to assess the in vitro differentiation capacity of human bone marrow-derived stem cells (hBMSCs) along retinal lineages. Mononuclear cells (MNC) were isolated from bone marrow (BM) and mobilized peripheral blood (mPB) using Ficoll-Paque density gradient centrifugation, and were sorted by magnetic-activated cell sorting (MACS) for specific stem cell subsets (CD34(+)CD38(+)/CD34(+)CD38(-)). These cells were then co-cultured on human retinal pigment epithelial cells (hRPE) for 7 days. The expression of stem cell, neural and retina-specific markers was examined by immunostaining, and the gene expression profiles were assessed after FACS separation of the co-cultured hBMSCs by quantitative reverse transcription polymerase chain reaction (qRT-PCR). Furthermore, in vitro functionality of the differentiated cells was analyzed by quantifying phagocytosis of CY5-labeled photoreceptor outer segments (POS). After 7 days of co-culture, hBMSCs adopted an elongated epithelial-like morphology and expressed RPE-specific markers, such as RPE65 and bestrophin. In addition, these differentiated cells were able to phagocytose OS, one of the main characteristics of native RPE cells. Our data demonstrated that human CD34(+)CD38(-) hBMSC may differentiate towards an RPE-like cell type in vitro and could become a new type of autologous donor cell for regenerative therapy in retinal degenerative diseases.

Molecular Classification of Ependymal Tumors across All CNS Compartments, Histopathological Grades, and Age Groups

Ependymal tumors across age groups are currently classified and graded solely by histopathology. It is, however, commonly accepted that this classification scheme has limited clinical utility based on its lack of reproducibility in predicting patients' outcome. We aimed at establishing a uniform molecular classification using DNA methylation profiling. Nine molecular subgroups were identified in a large cohort of 500 tumors, 3 in each anatomical compartment of the CNS, spine, posterior fossa, supratentorial. Two supratentorial subgroups are characterized by prototypic fusion genes involving RELA and YAP1, respectively. Regarding clinical associations, the molecular classification proposed herein outperforms the current histopathological classification and thus might serve as a basis for the next World Health Organization classification of CNS tumors.

Darwin's multicellularity: from neurotrophic theories and cell competition to fitness fingerprints

Metazoans have evolved ways to engage only the most appropriate cells for long-term tissue development and homeostasis. In many cases, competitive interactions have been shown to guide such cell selection events. In Drosophila, a process termed cell competition eliminates slow proliferating cells from growing epithelia. Recent studies show that cell competition is conserved in mammals with crucial functions like the elimination of suboptimal stem cells from the early embryo and the replacement of old T-cell progenitors in the thymus to prevent tumor formation. Moreover, new data in Drosophila has revealed that fitness indicator proteins, required for cell competition, are also involved in the culling of retinal neurons suggesting that 'fitness fingerprints' may play a general role in cell selection.

Cardiovascular-renal axis disorders in the domestic dog and cat: a veterinary consensus statement.

OBJECTIVES There is a growing understanding of the complexity of interplay between renal and cardiovascular systems in both health and disease. The medical profession has adopted the term "cardiorenal syndrome" (CRS) to describe the pathophysiological relationship between the kidney and heart in disease. CRS has yet to be formally defined and described by the veterinary profession and its existence and importance in dogs and cats warrant investigation. The CRS Consensus Group, comprising nine veterinary cardiologists and seven nephrologists from Europe and North America, sought to achieve consensus around the definition, pathophysiology, diagnosis and management of dogs and cats with "cardiovascular-renal disorders" (CvRD). To this end, the Delphi formal methodology for defining/building consensus and defining guidelines was utilised. METHODS Following a literature review, 13 candidate statements regarding CvRD in dogs and cats were tested for consensus, using a modified Delphi method. As a new area of interest, well-designed studies, specific to CRS/CvRD, are lacking, particularly in dogs and cats. Hence, while scientific justification of all the recommendations was sought and used when available, recommendations were largely reliant on theory, expert opinion, small clinical studies and extrapolation from data derived from other species. RESULTS Of the 13 statements, 11 achieved consensus and 2 did not. The modified Delphi approach worked well to achieve consensus in an objective manner and to develop initial guidelines for CvRD. DISCUSSION The resultant manuscript describes consensus statements for the definition, classification, diagnosis and management strategies for veterinary patients with CvRD, with an emphasis on the pathological interplay between the two organ systems. By formulating consensus statements regarding CvRD in veterinary medicine, the authors hope to stimulate interest in and advancement of the understanding and management of CvRD in dogs and cats. The use of a formalised method for consensus and guideline development should be considered for other topics in veterinary medicine.

Variable phenotypic expressivity in inbred retinal degeneration mouse lines: A comparative study of C3H/HeOu and FVB/N rd1 mice

PURPOSE Recent advances in optogenetics and gene therapy have led to promising new treatment strategies for blindness caused by retinal photoreceptor loss. Preclinical studies often rely on the retinal degeneration 1 (rd1 or Pde6b(rd1)) retinitis pigmentosa (RP) mouse model. The rd1 founder mutation is present in more than 100 actively used mouse lines. Since secondary genetic traits are well-known to modify the phenotypic progression of photoreceptor degeneration in animal models and human patients with RP, negligence of the genetic background in the rd1 mouse model is unwarranted. Moreover, the success of various potential therapies, including optogenetic gene therapy and prosthetic implants, depends on the progress of retinal degeneration, which might differ between rd1 mice. To examine the prospect of phenotypic expressivity in the rd1 mouse model, we compared the progress of retinal degeneration in two common rd1 lines, C3H/HeOu and FVB/N. METHODS We followed retinal degeneration over 24 weeks in FVB/N, C3H/HeOu, and congenic Pde6b(+) seeing mouse lines, using a range of experimental techniques including extracellular recordings from retinal ganglion cells, PCR quantification of cone opsin and Pde6b transcripts, in vivo flash electroretinogram (ERG), and behavioral optokinetic reflex (OKR) recordings. RESULTS We demonstrated a substantial difference in the speed of retinal degeneration and accompanying loss of visual function between the two rd1 lines. Photoreceptor degeneration and loss of vision were faster with an earlier onset in the FVB/N mice compared to C3H/HeOu mice, whereas the performance of the Pde6b(+) mice did not differ significantly in any of the tests. By postnatal week 4, the FVB/N mice expressed significantly less cone opsin and Pde6b mRNA and had neither ERG nor OKR responses. At 12 weeks of age, the retinal ganglion cells of the FVB/N mice had lost all light responses. In contrast, 4-week-old C3H/HeOu mice still had ERG and OKR responses, and we still recorded light responses from C3H/HeOu retinal ganglion cells until the age of 24 weeks. These results show that genetic background plays an important role in the rd1 mouse pathology. CONCLUSIONS Analogous to human RP, the mouse genetic background strongly influences the rd1 phenotype. Thus, different rd1 mouse lines may follow different timelines of retinal degeneration, making exact knowledge of genetic background imperative in all studies that use rd1 models.

Differentiation of Diabetic Macular Edema From Pseudophakic Cystoid Macular Edema by Spectral-Domain Optical Coherence Tomography.

PURPOSE: To differentiate diabetic macular edema (DME) from pseudophakic cystoid macular edema (PCME) based solely on spectral-domain optical coherence tomography (SD-OCT). METHODS: This cross-sectional study included 134 participants: 49 with PCME, 60 with DME, and 25 with diabetic retinopathy (DR) and ME after cataract surgery. First, two unmasked experts classified the 25 DR patients after cataract surgery as either DME, PCME, or mixed-pattern based on SD-OCT and color-fundus photography. Then all 134 patients were divided into two datasets and graded by two masked readers according to a standardized reading-protocol. Accuracy of the masked readers to differentiate the diseases based on SD-OCT parameters was tested. Parallel to the masked readers, a computer-based algorithm was established using support vector machine (SVM) classifiers to automatically differentiate disease entities. RESULTS: The masked readers assigned 92.5% SD-OCT images to the correct clinical diagnose. The classifier-accuracy trained and tested on dataset 1 was 95.8%. The classifier-accuracy trained on dataset 1 and tested on dataset 2 to differentiate PCME from DME was 90.2%. The classifier-accuracy trained and tested on dataset 2 to differentiate all three diseases was 85.5%. In particular, higher central-retinal thickness/retinal-volume ratio, absence of an epiretinal-membrane, and solely inner nuclear layer (INL)-cysts indicated PCME, whereas higher outer nuclear layer (ONL)/INL ratio, the absence of subretinal fluid, presence of hard exudates, microaneurysms, and ganglion cell layer and/or retinal nerve fiber layer cysts strongly favored DME in this model. CONCLUSIONS: Based on the evaluation of SD-OCT, PCME can be differentiated from DME by masked reader evaluation, and by automated analysis, even in DR patients with ME after cataract surgery. The automated classifier may help to independently differentiate these two disease entities and is made publicly available.