Supplementary Figure Legends 1-4 from Histone Deacetylases Are Required for Androgen Receptor Function in Hormone-Sensitive and Castrate-Resistant Prostate Cancer
Précis: We updated a clinical decision support tool integrating predicted visual field (VF) metrics from an artificial intelligence model and assessed clinician perceptions of the predicted VF metric in this usability study. Purpose: To evaluate clinician perceptions of a prototyped clinical decision support (CDS) tool that integrates visual field (VF) metric predictions from artificial intelligence (AI) models. Methods: Ten ophthalmologists and optometrists from the University of California San Diego participated in 6 cases from 6 patients, consisting of 11 eyes, uploaded to a CDS tool (“GLANCE”, designed to help clinicians “at a glance”). For each case, clinicians answered questions about management recommendations and attitudes towards GLANCE, particularly regarding the utility and trustworthiness of the AI-predicted VF metrics and willingness to decrease VF testing frequency. Main Outcome(s) and Measure(s): Mean counts of management recommendations and mean Likert scale scores were calculated to assess overall management trends and attitudes towards the CDS tool for each case. In addition, system usability scale scores were calculated. Results: The mean Likert scores for trust in and utility of the predicted VF metric and clinician willingness to decrease VF testing frequency were 3.27, 3.42, and 2.64, respectively (1=strongly disagree, 5=strongly agree). When stratified by glaucoma severity, all mean Likert scores decreased as severity increased. The system usability scale score across all responders was 66.1±16.0 (43rd percentile). Conclusions: A CDS tool can be designed to present AI model outputs in a useful, trustworthy manner that clinicians are generally willing to integrate into their clinical decision-making. Future work is needed to understand how to best develop explainable and trustworthy CDS tools integrating AI before clinical deployment.
Neurons use cell-adhesion molecules (CAMs) to interact with other neurons and the extracellular environment: the combination of CAMs specifies migration patterns, neuronal morphologies, and synaptic connections across diverse neuron types. Yet little is known regarding the intracellular signaling cascade mediating the CAM recognitions at the cell surface across different neuron types. In this study, we investigated the neural developmental role of Afadin 1–4 , a cytosolic adapter protein that connects multiple CAM families to intracellular F-actin. We introduced the conditional Afadin mutant 5 to an embryonic retinal Cre, Six3-Cre 6–8 . We reported that the mutants lead to the scrambled retinal neuron distribution, including Bipolar Cells (BCs), Amacrine Cells (ACs), and retinal ganglion cells (RGCs), across three cellular layers of the retina. This scrambled pattern was first reported here at neuron-type resolution. Importantly, the mutants do not display deficits for BCs, ACs, or RGCs in terms of neural fate specifications or survival. Additionally, the displayed RGC types still maintain synaptic partners with putative AC types, indicating that other molecular determinants instruct synaptic choices independent of Afadin. Lastly, there is a significant decline in visual function and mis-targeting of RGC axons to incorrect zones of the superior colliculus, one of the major retinorecipient areas. Collectively, our study uncovers a unique cellular role of Afadin in sorting retinal neuron types into proper cellular layers as the structural basis for orderly visual processing.
Background: Glaucoma is a group of chronic diseases that cause progressive damage to the optic nerve, resulting in irreversible and potentially debilitating visual loss. A unified, comprehensive and quantitative decision-making methodology is necessary to support clinicians and patients when conducting effective computer-aided glaucoma clinical diagnosis, monitoring, treatment and quality of life (QoL) assessment. Methods: We set out the functional requirements for a patient-centric computerized glaucoma treatment and care ecosystem with a 5- to 20-year time horizon. We evaluate three approaches used for glaucoma diagnosis, treatment and establishment of QoL targets: firstly, the Biomedical Model based on biophysical testing; secondly, conventional QoL assessment approach based on various patient-reported outcome (PRO) questionnaires; and thirdly, Outcomes models to evaluate healthcare based on analysis of Quality Adjusted Life Years (QALYs). Results: We identify many critical issues related to handling and analysis of glaucoma patient health data (technical, regulatory, security and privacy), as well as those related to the assessment of biological, psychological, and socioeconomic wellbeing, risk management, the ability to live independently, with adaptation to different cultures, languages and local healthcare delivery patterns. We address health planners, glaucoma research bodies and healthtech investors. We propose a blueprint for computerized actions required to improve treatment outcomes and to reduce costs while simultaneously providing individualized support to millions of glaucoma patients globally. Conclusions: Such patient-centric methodology must be based on interdisciplinary integration and mutual assistance from these three complementary approaches, as well as on their ongoing simultaneous improvements. To implement an effective healthcare decision support platform globally, all these challenges must be resolved. All this can be achieved in a consistent, cost-effective, high-quality manner.
Significance Delayed revascularization of ischemic neural tissue is a major impediment to preservation of function in central nervous system (CNS) diseases including stroke and ischemic retinopathies. The key mechanisms governing vascular recovery in ischemic CNS, including regulatory molecules governing transition from tissue injury to repair, are largely unknown. We report here on NF-E2-related factor 2 (Nrf2), a major stress-response transcription factor known for its cell-intrinsic cytoprotective function, in a novel capacity coordinating tissue repair and remodeling, including regulation of cell–cell crosstalk. Nrf2 activity in ischemic neurons reduces their resistance to reparative angiogenesis by suppressing expression of neuronal semaphorin 6A (Sema6A) and its antiangiogenic effects. Pharmacologic activation of Nrf2 or inhibition of Sema6A promote reparative angiogenesis in this ischemic setting, suggesting therapeutic avenues for ischemic retinopathies and other ischemic diseases.
ABSTRACT Optical coherence tomography (OCT) has gained wide adoption in biological and medical imaging due to its exceptional tissue penetration, 3D imaging speed and rich contrast. However, OCT plays a relatively small role in molecular and cellular imaging due to the lack of suitable biomolecular contrast agents. In particular, while the green fluorescent protein has provided revolutionary capabilities to fluorescence microscopy by connecting it to cellular functions such as gene expression, no equivalent reporter gene is currently available for OCT. Here we introduce gas vesicles, a unique class of naturally evolved gas-filled protein nanostructures, as the first genetically encodable OCT contrast agents. The differential refractive index of their gas compartments relative to surrounding aqueous tissue and their nanoscale motion enables gas vesicles to be detected by static and dynamic OCT at picomolar concentrations. Furthermore, the OCT contrast of gas vesicles can be selectively erased in situ with ultrasound, allowing unambiguous assignment of their location. In addition, gas vesicle clustering modulates their temporal signal, enabling the design of dynamic biosensors. We demonstrate the use of gas vesicles as reporter genes in bacterial colonies and as purified contrast agents in vivo in the mouse retina. Our results expand the utility of OCT as a unique photonic modality to image a wider variety of cellular and molecular processes.
