Abstract 367: Methods to enhance the optical resolution for 3D-SIM for the study of Hodgkin's lymphoma nuclei
Bibliographic record
Abstract
Abstract In spite of a great deal of knowledge already available, the precise higher order organization of chromatin is still a subject of an debate. Moreover, cancerous cells have an altered chromatin organization in comparison to their healthy counterparts. This is also the case for Hodgkin's lymphoma (HL) - a lymphoid malignancy of B cell origin. HL comprises two cell types, the Hodgkin cells and the diagnostic bi- or multinucleated Reed-Sternberg (RS) cells readily distinguishable from healthy lymphocytes. Patient stratitifcation has been proposed through the quantitative analysis of 3D nuclear telomere organization. With the advent of super resolution microscopy (SRM), further insights into the spatial organization of the cancer genome become feasible. This includes the study of chromatin arrangement with SRM. However, its application to HL remains limited due to technical difficulties: HL cells display thickness of >10µm resulting in light scattering and decreased signal-to-noise ratio. Structured Illumination Microscopy (SIM, a SRM type) in particular has advanced studies of the sub-cellular structures. It relies on projection of excitation pattern on to a fluorescently labeled sample. Sample's information is then shifted to a detectable band doubling the 3D resolution. Sample's refractive index homogeneity and counteracting photo-bleaching are both crucial for maintenance of the sharp illumination pattern and high-quality SIM, particularly in thick samples. Nevertheless, sample mounting media for SIM have not undergone a significant evolution since almost a decade. By identification and systematic comparison of non-hazardous components of mounting media we demonstrate increased sample's transparency and consequently improved SIM-quality. Using these novel sample clearing protocols we demonstrate high-resolution chromatin organization at ~120nm level in large RS cells of HL cell lines and in patient samples compared to lymphocytes. This work is of relevance of identification of new diagnostic structural biomarkers for HL. Citation Format: Aleksander T. Szczurek, Fabio Contu, Roberta Vanni, Hans Knecht, Nathalie Johnson, Tina Haliotis, Sabine Mai. Methods to enhance the optical resolution for 3D-SIM for the study of Hodgkin's lymphoma nuclei [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 367.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".