Microvascular geometry and differential permeability in the eye during inflammation revealed with dual channel multiphoton microscopy
Bibliographic record
Abstract
Microvascular permeability is a serious complication of systemic inflammation in critically ill patients; yet, no direct techniques exist to quantify this in vivo. To overcome this limitation, we investigated the use of multiphoton microscopy to evaluate fluorescent macromolecular gradients in the eye. Following the induction of systemic inflammation in a CD1 mouse, a bolus of high (250 KD FITC-dextran) and low (70 KD rhodamine-dextran) molecular weight fluorescent macromolecules was injected via the tail vein. The anesthetized mouse was positioned in such a way that different microvessels in the eye could be imaged directly using an upright microscope. The fluorophores were simultaneously excited at 840nm and a series of images including a spectral scan (480 to 680nm), an xt line scan (96 lines) and an x,y,z image stack were collected from the iris, cornea and limbal plexus at one hour intervals for four hours. A simple fluorescent gradient across the vessel wall was used as an index of microvascular permeability. In all microvessels, the LMW dye was more permeable. We found that the fluorescent gradient increased dramatically in the limbal plexus up to three hours then declined. This may indicate that circulating fluid pooled near the limbal plexus. Consistent with the thick walls and tight junctions of the iris microvessels, no significant fluorescent gradients were detected in this area. The cornea, containing a collagen filled stroma layer, was found to have both lateral and perpendicular fluorescent gradients. This work demonstrates that inflammation causes differential microvascular permeability in the mouse eye.
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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) | 0.001 | 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".