# Imaging Core

> **NIH NIH P30** · WASHINGTON UNIVERSITY · 2020 · $160,295

## Abstract

Project Summary.
The Imaging Resource Core will provide vision scientists at Washington University with access to state-of-the-
art instrumentation and technical support. The Core is centered on a fully-equipped histological laboratory
staffed by an experienced histotechnologist. The core has particular expertise in managing the unique
challenges of obtaining high quality images from ocular tissue. Tissue can be prepared for paraffin sectioning,
cryo-sectioning, or plastic embedding (for light or electron microscopy). In addition to conventional staining,
the Core offers in situ hybridization and immunocytochemistry services. In a nearby imaging suite are located
a Zeiss LSM800 confocal microscope (fitted with an Airy detector), an Olympus FV1000 confocal/multiphoton
instrument, a Nikon Eclipse Ti live cell imaging station, and a Leica fluorescence Macroscope. Support and
training on all instruments is provided by Core staff. Other major pieces of equipment managed by the Imaging
Core include a laser microdissection system and a small animal OCT system. Following appropriate training,
all services are available to Washington University vision scientists via on on-line scheduling system. This
well-utilized Resource Core has contributed significantly to the scientific productivity of the user group in the
past, and we expect heavy usage of Core resources to continue in the future.

## Key facts

- **NIH application ID:** 10019877
- **Project number:** 2P30EY002687-42
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Steven Bassnett
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $160,295
- **Award type:** 2
- **Project period:** 1997-04-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10019877

## Citation

> US National Institutes of Health, RePORTER application 10019877, Imaging Core (2P30EY002687-42). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10019877. Licensed CC0.

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