A new approach to non-mydriatic portable fundus imaging.

INTRODUCTION: The present study proposes a new hand-held non-mydriatic fundus camera for retinal imaging. The goal is to design a fundus camera which is equally effective in both clinical and telemedicine scenarios. AREAS COVERED: A new retinal illumination approach is proposed to address the main dilemma of the optical design, i.e. balancing efficacy with structural simplicity. This is achieved by symmetrical and co-axial placement of multiple illumination sources along the optical pathway. Each illumination source includes a white and a Near Infra-Red (NIR) LED, which are placed adjacent to each other. Hence, the camera can produce a view-finder with NIR illumination without the need for additional beam-splitters and filters. EXPERT OPINION: The proposed design blends the structural simplicity of the 'off-axis illumination with the wide field of view and uniform illumination of the 'ring' illumination. Moreover, the camera is designed to work with Android-based smartphones, which can easily be mounted and interfaced. The efficacy of the proposed camera is determined by ocular safety analysis and comparative evaluation with a table-top fundus camera. The results convincingly demonstrate the ability of the proposed camera as a primary driver of a wide-scale screening program in both clinical and remote resource constraint environments.

A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles.

We previously piloted the concept of a Connectivity Map (CMap), whereby genes, drugs, and disease states are connected by virtue of common gene-expression signatures. Here, we report more than a 1,000-fold scale-up of the CMap as part of the NIH LINCS Consortium, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that we term L1000. We show that L1000 is highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts. We further show that the expanded CMap can be used to discover mechanism of action of small molecules, functionally annotate genetic variants of disease genes, and inform clinical trials. The 1.3 million L1000 profiles described here, as well as tools for their analysis, are available at https://clue.io.

Reduced-representation Phosphosignatures Measured by Quantitative Targeted MS Capture Cellular States and Enable Large-scale Comparison of Drug-induced Phenotypes.

Profiling post-translational modifications represents an alternative dimension to gene expression data in characterizing cellular processes. Many cellular responses to drugs are mediated by changes in cellular phosphosignaling. We sought to develop a common platform on which phosphosignaling responses could be profiled across thousands of samples, and created a targeted MS assay that profiles a reduced-representation set of phosphopeptides that we show to be strong indicators of responses to chemical perturbagens.To develop the assay, we investigated the coordinate regulation of phosphosites in samples derived from three cell lines treated with 26 different bioactive small molecules. Phosphopeptide analytes were selected from these discovery studies by clustering and picking 1 to 2 proxy members from each cluster. A quantitative, targeted parallel reaction monitoring assay was developed to directly measure 96 reduced-representation probes. Sample processing for proteolytic digestion, protein quantification, peptide desalting, and phosphopeptide enrichment have been fully automated, making possible the simultaneous processing of 96 samples in only 3 days, with a plate phosphopeptide enrichment variance of 12%. This highly reproducible process allowed ∼95% of the reduced-representation phosphopeptide probes to be detected in ∼200 samples.The performance of the assay was evaluated by measuring the probes in new samples generated under treatment conditions from discovery experiments, recapitulating the observations of deeper experiments using a fraction of the analytical effort. We measured these probes in new experiments varying the treatments, cell types, and timepoints to demonstrate generalizability. We demonstrated that the assay is sensitive to disruptions in common signaling pathways (e.g. MAPK, PI3K/mTOR, and CDK). The high-throughput, reduced-representation phosphoproteomics assay provides a platform for the comparison of perturbations across a range of biological conditions, suitable for profiling thousands of samples. We believe the assay will prove highly useful for classification of known and novel drug and genetic mechanisms through comparison of phosphoproteomic signatures.