Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

An in vitro system for modeling brain reactive responses and changes in neuroprosthetic device impedance.

Currently available methods for analyzing the structural properties of neural tissue are limited by the frequency at which data can be collected and by the need to sacrifice the specimen to correlate histology with other data. Electrical impedance spectroscopy (EIS) can be used to complement conventional histological and imaging-based methods by measuring real-time electrical data that can be ascribed to changes in tissue composition and structure. This report describes an impedance-based method for the analysis and modeling of the electrical properties of three-dimensional neural tissue constructs in vitro. This model system was used to assess the effects of cell density, type and organization on neuroprosthetic device electrode performance.

Advanced imaging of multiple mRNAs in brain tissue using a custom hyperspectral imager and multivariate curve resolution.

Simultaneous imaging of multiple cellular components is of tremendous importance in the study of complex biological systems, but the inability to use probes with similar emission spectra and the time consuming nature of collecting images on a confocal microscope are prohibitive. Hyperspectral imaging technology, originally developed for remote sensing applications, has been adapted to measure multiple genes in complex biological tissues. A spectral imaging microscope was used to acquire overlapping fluorescence emissions from specific mRNAs in brain tissue by scanning the samples using a single fluorescence excitation wavelength. The underlying component spectra obtained from the samples are then separated into their respective spectral signatures using multivariate analyses, enabling the simultaneous quantitative measurement of multiple genes either at regional or cellular levels.

Mapping behaviorally relevant neural circuits with immediate-early gene expression.

Immediate-early genes have gained widespread popularity as activity markers for mapping neuronal circuits involved in specific behaviors in many different species. In situ immediate early gene detection methods provide cellular level resolution, a major benefit for mapping neuronal networks. Recent advances using fluorescence in situ hybridization also afford temporal resolution, enabling within-animal activity maps for two distinct behaviors. Moreover, use of transgenic mice with fluorescent reporter proteins driven by immediate early gene promoters is enabling repeated measurements, over long time scales, of cortical activity within the same animal. These methodological innovations, coupled with recent advances in fluorescence imaging and probe development, will enable large scale mapping of behaviorally relevant circuits with temporal and three-dimensional spatial resolution in experimental animals.

Selective cytokine inhibitory drugs with enhanced antiangiogenic activity control tumor growth through vascular inhibition.

Selective cytokine inhibitory drugs (SelCIDs) are a novel class of phosphodiesterase 4 inhibitors discovered during a thalidomide analog discovery program. These analogs were evaluated for their ability to inhibit tumor angiogenesis, vascularity, and growth. Two analogs (CC-7034 and CC-9088) were identified that had enhanced antiangiogenic activity in Matrigel assays compared with parental thalidomide. These analogs also inhibited the growth of established K1735 and RENCA murine tumors. Tumors whose growth was suppressed by SelCID treatment exhibited decreased vessel density together with increased tumor cell hypoxia and death. The decrease in vascularity produced by SelCID treatment is attributed to a selective loss of vessels devoid of pericyte coverage, suggesting that these agents target immature tumor vessels. That tumor cell death was localized to relatively avascular or hypoxic areas, coupled with the fact that none of the analogs was cytotoxic in vitro against the tumor cells, demonstrates that these analogs are novel antivascular agents with potent antitumor activity.