Structure illumination microscopy imaging of lipid vesicles in live bacteria with naphthalimide-appended organometallic complexes
Bibliographic record
Abstract
There is a lack of molecular probes for imaging bacteria, in comparison to the array of such tools available for the imaging of mammalian cells. Here, organometallic molecular probes have been developed and assessed for bacterial imaging, designed to have the potential to support multiple imaging modalities. The chemical structure of the probes is designed around a metal-naphthalimide structure. The 4-amino-1,8-naphthalimide moiety, covalently appended through a pyridine ancillary ligand, acts as a luminescent probe for super-resolution microscopy. On the other hand, the metal centre, rhenium(i) or platinum(ii) in the current study, enables techniques such as nanoSIMS. While the rhenium(i) complex was not sufficiently stable to be used as a probe, the platinum(ii) analogue showed good chemical and biological stability. Structured illumination microscopy (SIM) imaging on live Bacillus cereus confirmed the suitability of the probe for super-resolution microscopy. NanoSIMS analysis was used to monitor the uptake of the platinum(ii) complex within the bacteria and demonstrate the potential of this chemical architecture to enable multimodal imaging. The successful combination of these two moieties introduces a platform that could lead to a versatile range of multi-functional probes for bacteria.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".