Use of Magnetotactic Bacteria as an MRI Contrast Agent for In Vivo Tracking of Adoptively Transferred Immune Cells
Bibliographic record
Abstract
Abstract Purpose In vivo immune cell tracking using MRI is a valuable tool for studying the mechanisms underlying successful cancer therapies. Current cell labeling methods using superparamagnetic iron oxide (SPIO) lack the specificity and persistence needed to track the fate and location of transplanted cells long-term. Magnetospirillium magneticum is a commercially available, iron-producing bacterium that can be taken up by, and live harmoniously within, mammalian cells as magneto-endosymbionts (MEs). MEs have shown promise as labeling agents for in vivo stem and cancer cell tracking but have yet to be evaluated in immune cells. This pilot study examined ME labeling in myeloid-derived suppressor cells (MDSCs), cytotoxic T lymphocytes (CTLs) and dendritic cells (DCs) and its effects on cell purity, function and MRI contrast. Procedures: MDSCs, CTLs and DCs were incubated with MEs at various ME labelling ratios (MLR) and various biological metrics and iron uptake were assessed. For in vivo imaging, MDSCs were labeled overnight with either MEs or SPIO (Molday ION Rhodamine B) and injected into C3 tumor-bearing mice via tail vein injection 24 days post-implant and scanned daily with MRI for one week to assess cellular quantification. Results Following incubations MDSCs contained 0.62 and 2.22 pg Fe/ cell. CTLs achieved Fe loading of < 0.5 pg/ cell and DCs achieved Fe loading of ~ 1.4pg/cell. The suppressive functionality of MDSCs at 1000MLR was not affected by ME labeling but was affected at 2000MLR. Markers of CTL dysfunction were not markedly affected by ME labeling, nor were DC markers. In vivo data demonstrated that the MDSCs labeled with MEs generated sufficient contrast to be detectable using TurboSPI, similar to SPIO-labeled cells. Conclusions Cells can be labeled with pre-clinically relevant amounts of MEs without compromising cell viability. Care must be taken at higher concentrations of MEs, which may affect the functional activity and/or morphology of some cell types. Immune cells with minimal phagocytic behaviour have much lower iron content per cells after incubation with MEs vs SPIO; however, MEs can successfully be used as a contrast agent for phagocytic immune cells.
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.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".