Noninvasive assessment of the iridial microcirculation in rats using sidestream dark field imaging
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sidestream dark field imaging represents a novel, noninvasive method to study the microcirculation in humans and animals. To-date, it has been used extensively in various peripheral tissues (e.g. sublingual area, intestinal mucosa), however no data for the ocular vasculature, including the iridial microcirculation, are currently available. Therefore, the aim of this study was to examine the reliability and reproducibility of sidestream dark field imaging within the iridial microcirculation in experimental animals. Male Lewis rats were anaesthetized and the iris microvasculature was observed using an sidestream dark field probe gently placed against a cover slip covering the right eye. All video sequences recorded were analysed off-line by using AVA 3.0 software (MicroVision Medical, Amsterdam, The Netherlands). Results are expressed as mean (±SE) or median (interquartile range). Clear images were recorded from each animal and the total number of analysable video sequences was 50. All raw data for selected vessel density parameters passed normality test. The total all and small vessel density (in mm mm(-2) ) were 22,6 (±0,58) and 19,6 (±0,68), respectively. The perfused all and small vessel density were 20,9 (±0,61) and 19,1 (±0,65), respectively. The mean values of all iris vessel density parameters are shown in Figure 4. The DeBacker Score (n/mm) was 15,2 (±0,45), the proportion of perfused vessel was 94,5% (89,8-99,1%), and the MFI was 3 points (3-3). Taken together, these results indicate that SDF imaging provides a reliable and noninvasive method to examine the iridial microvascular bed in vivo and, thus, may provide unique opportunities for the study of the iridial vascular network in various experimental and clinical settings and disease models.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it