Label-free two-photon imaging of mitochondrial activity in murine macrophages stimulated with bacterial and viral ligands
Bibliographic record
Abstract
Mitochondria are the metabolic hub of the cell, playing a central role in regulating immune responses. Dysfunction of mitochondrial reprogramming can occur during bacterial and viral infections compromising hosts' immune signaling. Comparative evaluation of these alterations in response to bacterial and viral ligands can provide insights into a cell's ability to mount pathogen-specific responses. In this study, we used two-photon excitation fluorescence (TPEF) imaging to quantify reduced nicotinamide adenine dinucleotide phosphate (NAD(P)H) and flavin adenine dinucleotide (FAD) levels in the cell and to calculate the optical redox ratio (ORR), an indicator of mitochondrial dysfunction. Analyses were performed on RAW264.7 cells and murine bone marrow derived macrophages (BMM) stimulated with bacterial (LPS) and viral (Poly(I:C)) ligands. Responses were cell type dependent, with primary cells having significantly higher levels of FAD and higher oxygen consumption rates suggesting BMM may be more dependent on mitochondrial metabolism. Our findings also suggest that FAD-TPEF intensity may be a better predictor of mitochondrial activity and localization since it demonstrates unique mitochondrial clustering patterns in LPS vs. Poly(I:C) stimulated macrophages. Collectively, we demonstrate that TPEF imaging is a powerful label-free approach for quantifying changes in mitochondrial function and organization in macrophages following bacterial and viral stimuli.
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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 | 0.001 |
| 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".