Distribution of aquaporin genes and selection of individual reference genes for quantitative real-time RT-PCR analysis in multiple tissues of the mouse
Bibliographic record
Abstract
Aquaporins (AQPs) are a family of water-transporting proteins that are selectively expressed in epithelial, endothelial, and many other cell types of various tissues, where they play important physiological functions. However, the accurate distribution of AQP gene expression has not yet been examined in various tissues of the mouse. We first evaluated the tissue distribution of AQP gene expression using tongue, nasal epithelium, bronchus, trachea, lung, esophagus, stomach, ileum, transverse colon, liver, pancreas, whole blood, thigh muscle, spinal cord, brain, thoracic aorta, heart, kidney, thymus, spleen, skin, eye, and testis of the mouse. Furthermore, for a quantitative analysis, we selected appropriate reference genes for normalized qRT-PCR data in various tissues. The stability of the reference genes was assessed using NormFinder. The stably expressed genes identified in the present study were 18s rRNA. When 18s rRNA was used, as the best reference gene in the present study, the genes for AQPs 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, and 12 were notably expressed in the eye, lung, testis, eye, spinal cord, trachea, kidney, testis, testis, testis, testis, and pancreas. These results, regarding the distribution of AQPs, suggest that AQPs may be involved in various physiological and pathophysiological processes.
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 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".