Single Cell Expression Analysis for Understanding the Development of Glaucoma

Glaucoma is characterized as a group of eye diseases where the progressive damage of neurons, particularly Retinal Ganglion Cells (RGCs), leads to vision loss. This disease affects more than 70 million people worldwide, with approximately 10% being bilaterally blind, making it the leading cause of irreversible blindness in the world. The initiation and progression of the disease is still unknown, but studies have suggested the involvement of particular cell types in the retina that relate to the pathogenesis of glaucoma. Single cell RNA sequencing (RNA-seq) analysis is a new technology that provides insight into the gene expression profiles of different cell types. In this study, we employed it to elucidate the transcriptomic changes in various cell types during glaucoma progression. ABCA1-/- mice were used as a normal tension glaucoma model. Single cell RNA-seq experiments were conducted on three wild type (WT) and five knockout (KO) retinal tissues. The data of 62,479 cells were integrated and major cell types were identified, including Müller glia, astrocytes, microglia and RGCs. Ontological analysis suggested strong activation of neuroinflammation and senescence related pathways in KO samples, with specific pathways identified affecting certain cell types. Evidence of macrophage invasion further suggests a knockout-induced inflammatory response, accompanied by sub-type specific RGC degeneration due to excitotoxicity. P2Y6-/- mice were used as a high intraocular pressure (IOP) glaucoma model. 105,772 cells from three WT and three KO retinal tissues were analysed using single cell RNA-seq, with major cell types identified such as RGCs and glial cells. Neuroinflammation and senescence pathways activation was again observed, along with angiogenesis, hypoxia and fibrosis activities activated in knockout glial population. pathogenesis, thus provided data to support future interests in developing potential therapeutical targets in the area. pathogenesis, thus provided data to support future interests in developing potential therapeutical targets in the area

One-Step Estimation of Differentiable Hilbert-Valued Parameters

We present estimators for smooth Hilbert-valued parameters, where smoothness is characterized by a pathwise differentiability condition. When the parameter space is a reproducing kernel Hilbert space, we provide a means to obtain efficient, root-n rate estimators and corresponding confidence sets. These estimators correspond to generalizations of cross-fitted one-step estimators based on Hilbert-valued efficient influence functions. We give theoretical guarantees even when arbitrary estimators of nuisance functions are used, including those based on machine learning techniques. We show that these results naturally extend to Hilbert spaces that lack a reproducing kernel, as long as the parameter has an efficient influence function. However, we also uncover the unfortunate fact that, when there is no reproducing kernel, many interesting parameters fail to have an efficient influence function, even though they are pathwise differentiable. To handle these cases, we propose a regularized one-step estimator and associated confidence sets. We also show that pathwise differentiability, which is a central requirement of our approach, holds in many cases. Specifically, we provide multiple examples of pathwise differentiable parameters and develop corresponding estimators and confidence sets. Among these examples, four are particularly relevant to ongoing research by the causal inference community: the counterfactual density function, dose-response function, conditional average treatment effect function, and counterfactual kernel mean embedding

Parallel machine architecture and compiler design facilities

The objective is to provide an integrated simulation environment for studying and evaluating various issues in designing parallel systems, including machine architectures, parallelizing compiler techniques, and parallel algorithms. The status of Delta project (which objective is to provide a facility to allow rapid prototyping of parallelized compilers that can target toward different machine architectures) is summarized. Included are the surveys of the program manipulation tools developed, the environmental software supporting Delta, and the compiler research projects in which Delta has played a role

A Theory of Tagged Objects (Artifact)

A compiler and interpreter for Wyvern programming language written in Java and hosted on http://github.com/wyvernlang/wyvern and some sample programs (.wyv) including the main example from the paper in borderedwindow.wyv. We also include an extract of all the unit tests of which a large number may be designed to fail -- therefore they are best run using JUnit which can be done by checking out the source tree from the GitHub project link above

Positive Education at The Shipley School

Positive education, a unique blend of academic learning and positive psychology theory on well-being, is becoming increasingly important in today’s educational system, as mental disorders like anxiety and depression continue to increase in schools. Located in Bryn Mawr, Pennsylvania, The Shipley School, an independent PK-12 school, is an early adopter of positive education. In August 2017, Shipley led a three-day positive psychology retreat for all of its colleagues (teachers and staff); 25 self-selected colleagues, known as trained trainers, received an additional two days of training to guide them towards becoming thought leaders at Shipley. Preliminary evidence suggests that student’s perceptions of their teachers’ well-being may be associated with student well-being at Shipley. Additionally, the positive psychology retreat seems to have enhanced positive relationships among colleagues while decreasing loneliness and negative emotions. Per colleague feedback, active constructive responding, gratitude, mindfulness, optimism/thinking traps, and strengths appear to be the most salient skills taught at the retreat. As a result, we have developed onboarding plan recommendations for new colleagues encompassing the teaching of these five skills in small-group settings led by the trained trainers. We believe that Shipley is well on its way to becoming a leading model for positive education

Broadband energy-efficient optical modulation by hybrid integration of silicon nanophotonics and organic electro-optic polymer

Silicon-organic hybrid integrated devices have emerging applications ranging from high-speed optical interconnects to photonic electromagnetic-field sensors. Silicon slot photonic crystal waveguides (PCWs) filled with electro-optic (EO) polymers combine the slow-light effect in PCWs with the high polarizability of EO polymers, which promises the realization of high-performance optical modulators. In this paper, a broadband, power-efficient, low-dispersion, and compact optical modulator based on an EO polymer filled silicon slot PCW is presented. A small voltage-length product of V{\pi}*L=0.282Vmm is achieved, corresponding to an unprecedented record-high effective in-device EO coefficient (r33) of 1230pm/V. Assisted by a backside gate voltage, the modulation response up to 50GHz is observed, with a 3-dB bandwidth of 15GHz, and the estimated energy consumption is 94.4fJ/bit at 10Gbit/s. Furthermore, lattice-shifted PCWs are utilized to enhance the optical bandwidth by a factor of ~10X over other modulators based on non-band-engineered PCWs and ring-resonators.Comment: 12 pages, 4 figures, SPIE Photonics West Conference 201