Design and Implementation of a Custom Built Optical Projection Tomography System
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Optical projection tomography (OPT) is an imaging modality that has, in the last decade, answered numerous biological questions owing to its ability to view gene expression in 3 dimensions (3D) at high resolution for samples up to several cm(3). This has increased demand for a cabinet OPT system, especially for mouse embryo phenotyping, for which OPT was primarily designed for. The Medical Research Council (MRC) Technology group (UK) released a commercial OPT system, constructed by Skyscan, called the Bioptonics OPT 3001 scanner that was installed in a limited number of locations. The Bioptonics system has been discontinued and currently there is no commercial OPT system available. Therefore, a few research institutions have built their own OPT system, choosing parts and a design specific to their biological applications. Some of these custom built OPT systems are preferred over the commercial Bioptonics system, as they provide improved performance based on stable translation and rotation stages and up to date CCD cameras coupled with objective lenses of high numerical aperture, increasing the resolution of the images. Here, we present a detailed description of a custom built OPT system that is robust and easy to build and install. Included is a hardware parts list, instructions for assembly, a description of the acquisition software and a free download site, and methods for calibration. The described OPT system can acquire a full 3D data set in 10 minutes at 6.7 micron isotropic resolution. The presented guide will hopefully increase adoption of OPT throughout the research community, for the OPT system described can be implemented by personnel with minimal expertise in optics or engineering who have access to a machine shop.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it