Morphological and Molecular Defects in Human Three-Dimensional Retinal Organoid Model of X-Linked Juvenile Retinoschisis

X-linked juvenile retinoschisis (XLRS), linked to mutations in the RS1 gene, is a degenerative retinopathy with a retinal splitting phenotype. We generated human induced pluripotent stem cells (hiPSCs) from patients to study XLRS in a 3D retinal organoid in vitro differentiation system. This model recapitulates key features of XLRS including retinal splitting, defective retinoschisin production, outer-segment defects, abnormal paxillin turnover, and impaired ER-Golgi transportation. RS1 mutation also affects the development of photoreceptor sensory cilia and results in altered expression of other retinopathy-associated genes. CRISPR/Cas9 correction of the disease-associated C625T mutation normalizes the splitting phenotype, outer-segment defects, paxillin dynamics, ciliary marker expression, and transcriptome profiles. Likewise, mutating RS1 in control hiPSCs produces the disease-associated phenotypes. Finally, we show that the C625T mutation can be repaired precisely and efficiently using a base-editing approach. Taken together, our data establish 3D organoids as a valid disease model

Translational Retinal Research and Therapies.

The following review summarizes the state of the art in representative aspects of gene therapy/translational medicine and evolves from a symposium held at the School of Veterinary Medicine, University of Pennsylvania on November 16, 2017 honoring Dr. Gustavo Aguirre, recipient of ARVO's 2017 Proctor Medal. Focusing on the retina, speakers highlighted current work on moving therapies for inherited retinal degenerative diseases from the laboratory bench to the clinic

Image-Processing Techniques for the Creation of Presentation-Quality Astronomical Images

The quality of modern astronomical data, the power of modern computers and the agility of current image-processing software enable the creation of high-quality images in a purely digital form. The combination of these technological advancements has created a new ability to make color astronomical images. And in many ways it has led to a new philosophy towards how to create them. A practical guide is presented on how to generate astronomical images from research data with powerful image-processing programs. These programs use a layering metaphor that allows for an unlimited number of astronomical datasets to be combined in any desired color scheme, creating an immense parameter space to be explored using an iterative approach. Several examples of image creation are presented. A philosophy is also presented on how to use color and composition to create images that simultaneously highlight scientific detail and are aesthetically appealing. This philosophy is necessary because most datasets do not correspond to the wavelength range of sensitivity of the human eye. The use of visual grammar, defined as the elements which affect the interpretation of an image, can maximize the richness and detail in an image while maintaining scientific accuracy. By properly using visual grammar, one can imply qualities that a two-dimensional image intrinsically cannot show, such as depth, motion and energy. In addition, composition can be used to engage viewers and keep them interested for a longer period of time. The use of these techniques can result in a striking image that will effectively convey the science within the image, to scientists and to the public.Comment: 104 pages, 38 figures, submitted to A

Melting temperature of graphene

We present an approach to the melting of graphene based on nucleation theory for a first order phase transition from the 2D solid to the 3D liquid via an intermediate quasi-2D liquid. The applicability of nucleation theory, supported by the results of systematic atomistic Monte Carlo simulations, provides an intrinsic definition of the melting temperature of graphene, $T_m$, and allows us to determine it. We find $T_m \simeq 4510$ K, about 250 K higher than that of graphite using the same interatomic interaction model. The found melting temperature is shown to be in good agreement with the asymptotic results of melting simulations for finite disks and ribbons of graphene. Our results strongly suggest that graphene is the most refractory of all known materials

Wavelet domain Bayesian denoising of string signal in the cosmic microwave background

An algorithm is proposed for denoising the signal induced by cosmic strings in the cosmic microwave background (CMB). A Bayesian approach is taken, based on modeling the string signal in the wavelet domain with generalized Gaussian distributions. Good performance of the algorithm is demonstrated by simulated experiments at arcminute resolution under noise conditions including primary and secondary CMB anisotropies, as well as instrumental noise.Comment: 16 pages, 11 figures. Version 2 matches version accepted for publication in MNRAS. Changes include substantial clarifications on our approach and a significant reduction of manuscript lengt

Validating Variational Bayes Linear Regression Method With Multi-Central Datasets.

PurposeTo validate the prediction accuracy of variational Bayes linear regression (VBLR) with two datasets external to the training dataset.MethodThe training dataset consisted of 7268 eyes of 4278 subjects from the University of Tokyo Hospital. The Japanese Archive of Multicentral Databases in Glaucoma (JAMDIG) dataset consisted of 271 eyes of 177 patients, and the Diagnostic Innovations in Glaucoma Study (DIGS) dataset includes 248 eyes of 173 patients, which were used for validation. Prediction accuracy was compared between the VBLR and ordinary least squared linear regression (OLSLR). First, OLSLR and VBLR were carried out using total deviation (TD) values at each of the 52 test points from the second to fourth visual fields (VFs) (VF2-4) to 2nd to 10th VF (VF2-10) of each patient in JAMDIG and DIGS datasets, and the TD values of the 11th VF test were predicted every time. The predictive accuracy of each method was compared through the root mean squared error (RMSE) statistic.ResultsOLSLR RMSEs with the JAMDIG and DIGS datasets were between 31 and 4.3 dB, and between 19.5 and 3.9 dB. On the other hand, VBLR RMSEs with JAMDIG and DIGS datasets were between 5.0 and 3.7, and between 4.6 and 3.6 dB. There was statistically significant difference between VBLR and OLSLR for both datasets at every series (VF2-4 to VF2-10) (P < 0.01 for all tests). However, there was no statistically significant difference in VBLR RMSEs between JAMDIG and DIGS datasets at any series of VFs (VF2-2 to VF2-10) (P > 0.05).ConclusionsVBLR outperformed OLSLR to predict future VF progression, and the VBLR has a potential to be a helpful tool at clinical settings

Hubble Space Telescope and Ground-Based Observations of Type Ia Supernovae at Redshift 0.5: Cosmological Implications

We present observations of the Type Ia supernovae (SNe) 1999M, 1999N, 1999Q, 1999S, and 1999U, at redshift z~0.5. They were discovered in early 1999 with the 4.0~m Blanco telescope at Cerro Tololo Inter-American Observatory by the High-z Supernova Search Team (HZT) and subsequently followed with many ground-based telescopes. SNe 1999Q and 1999U were also observed with the Hubble Space Telescope. We computed luminosity distances to the new SNe using two methods, and added them to the high-z Hubble diagram that the HZT has been constructing since 1995. The new distance moduli confirm the results of previous work. At z~0.5, luminosity distances are larger than those expected for an empty universe, implying that a ``Cosmological Constant,'' or another form of ``dark energy,'' has been increasing the expansion rate of the Universe during the last few billion years.Comment: 68 pages, 22 figures. Scheduled for the 01 February 2006 issue of Ap.J. (v637