High‐Resolution Intravital NADH Fluorescence Microscopy Allows Measurements of Tissue Bioenergetics in Rat Ileal Mucosa
Bibliographic record
Abstract
OBJECTIVES: NADH fluorescence microscopy has been used as an index of the metabolic state of tissue but is associated with various obstacles such as low spatial resolution and quenching effects of blood pigments that prevent reliable monitoring of tissue bioenergetics. The objective of this study was to develop a system to monitor tissue bioenergetics in vivo using NADH fluorescence microscopy in the rat ileal mucosa. MATERIALS AND METHODS: Using an inverted microscope with an epifluorescence unit and an intensified charge-coupled device camera, NADH fluorescence images were visualized. Fluorescence intensity was measured of beta-NADH solutions at varying concentration (n = 6) and pH (n = 3) and in ex vivo (n = 6) and in vivo (n = 6) preparations of ileal mucosa of Sprague-Dawley rats anesthetized with isoflurane. RESULTS: Intravital fluorescence microscopy reveals a map of the microcirculation that permits visualization of NADH fluorescence and intercapillary areas. The system was adjusted so a linear relationship between physiological concentrations of beta-NADH and fluorescence was achieved (r(2) = 0.98, p < .0001). Decreasing the pH of the solution had no effect on fluorescence intensity and fluorescence intensity in an anoxic ex vivo ileal segment was similar to that of the in vivo ileum after ischemia. Ischemia also resulted in spatial heterogeneity that was abolished by the addition of a 550-nm LP filter. CONCLUSIONS: With this system, intravital NADH fluorescence microscopy provides the high resolution necessary to reliably monitor tissue bioenergetics in the rat ileal mucosa.
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 | 0.000 | 0.001 |
| 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".