Synthesis, Characterization, and Application of Metal-chelating Polymers for Mass Cytometric Bioassays
Bibliographic record
Abstract
This thesis describes the synthesis, characterization, and application of metal-chelating polymers for mass-cytometric bioassays. Mass cytometry is a cell characterization technique in which cells are injected individually into an ICP-MS detector. Signal is provided by staining cell-surface or intracellular antigens with metal-labeled antibodies (Abs). These Abs are labeled through the covalent attachment of metal-chelating polymers which carry multiple copies of a lanthanide isotope.\nIn this work, my first goal was to develop a facile, straightforward synthesis of a new generation of metal-chelating polymers. The synthesis began with reversible addition-fragmentation chain transfer polymerization, and was followed by numerous post-polymerization pendant group transformations to introduce DTPA lanthanide chelators to every repeat unit, and a maleimide at the end of the chain. \nThe second goal was to apply these metal-chelating polymers in bioassay experiments. The DTPA groups were loaded with lanthanide ions, and the maleimide group was used to covalently attach the polymer to an Ab. This goat anti-mouse conjugate was found to carry an average of 2.4 ± 0.3 polymer chains. Then, primary Ab conjugates were prepared and used in an 11-plex mass cytometry assay in the characterization of umbilical cord blood cells.\nThe third goal was to expand the multiplexity of the assay. In current technology, the number of Abs that can be monitored simultaneously is limited to the 31 commercially available, stable lanthanide isotopes. Thus, I had an interest in preparing metal-chelating polymers that could carry other metals in the 100-220 amu range. I synthesized polymers with four different polyaminocarboxylate ligands, and investigated the loading of palladium and platinum ions into these polymers. Polymer-Ab conjugates prepared with palladium- and platinum-loaded polymers gave curious results, in that only dead cells were recognized.\nThe fourth goal was to create dual-purpose Ab tags. My approach was to synthesize polymers similar to those described above, but which also carried two to six fluorescent dyes. Polymer-Ab conjugates prepared with four different dye-labeled polymers gave mixed results. Two of the four conjugates performed well in FACS and mass cytometric assays, but the other two did not. Further experiments are needed to overcome this problem.
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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".