Enabling Indium Channels for Mass Cytometry by Using Reinforced Cyclam-Based Chelating Polylysine
Bibliographic record
Abstract
The synthesis of a polylysine polymer functionalized with the previously reported astonishingly inert [In( cb-te2pa )] + chelate was performed. A biotin end group allowed the conjugation to biotinylated beads by the intermediary of a fluorescein isothiocyanate/neutravidin receptor. High quality imaging mass cytometry trials, based on 115 In detection were performed to highlight the behavior of the material. Anti-CD20 antibody was labeled by the so-obtained In(III)-modified polylysine using the biotin/neutravidin interaction. Ramos (CD20[+]) and HL-60 (CD20[−]) cell lines were costained with the In(III)-modified bioconjugate by finding the best staining conditions. Both immunofluorescence microscopy (IF-M) and mass cytometry analyses confirmed the specific binding of anti-CD20 onto Ramos cells. CyTOF histograms constructed on the 115 In detection allowed us to define and to separate, with a good signal-to-noise ratio, two populations (Ramos and HL-60). The inertness of In(III)-MCP-NAv over a three-month storage period was proved by performing new functionality tests involving Jurkat cells (CD20[−]) and multiparametric trials involving the 115 In channel. The results ensure a promising future use of the previously announced [In( cb-te2pa )] + complex-based polymers for mass cytometry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".