Quantifying colocalization of a conditionally active transcription factor FOXP3 in three-dimensional cellular space
Bibliographic record
Abstract
Biological macromolecular interactions between proteins, transcription factors, DNA and other types of biomolecules, are fundamentally important to several cellular and biological processes. 3D Multi-channel confocal microscopy and colocalization analysis of fluorescent signals have proven to be invaluable tools for detecting such molecular interactions. The aim of this work was to quantify colocalization of the FOXP3 transcription factor in 3D cellular space generated from the confocal 3D image sets. 293T cells transfected with a conditionally active form of FOXP3 were stained for nuclei with Hoechst, for FOXP3 with anti-FOXP3 conjugated to PE, and 4-hydroxytamoxifen used as protein translocation and activation agent. Since the protein signal was weak and nonspecific intensity contributions were strong, it was difficult to perform colocalization analysis and estimate colocalization quantities. We performed 3D restoration by deconvolution method on the confocal images using experimentally measured point spread functions (PSFs) and subsequently a color shift correction. The deconvolution method eliminated nonspecific intensity contributions originating from PSF imposed by optical microscopy diffraction resolution limits and noise since these factors significantly affected colocalization analysis and quantification. Visual inspection of the deconvolved 3D image suggested that the FOXP3 molecules are predominantly colocalized within the nuclei although the fluorescent signals from FOXP3 molecules were also present in the cytoplasm. A close inspection of the scatter plot (colocalization map) and correlation quantities such as the Pearsons and colocalization coefficients showed that the fluorescent signals from the FOXP3 molecules and DNA are strongly correlated. In conclusion, our colocalization quantification approach confirms the preferential association of the FOXP3 molecules with the DNA despite the presence of fluorescent signals from the former one both in the nuclei and cytoplasm.
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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 | 0.000 | 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 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".