Olfactory receptors contribute to progression of kidney fibrosis
Bibliographic record
Abstract
Olfactory receptors (ORs) which are mainly known as odor-sensors in the olfactory epithelium are shown to be expressed in several non-sensory tissues. Despite the specified role of some of these receptors in normal physiology of the kidney, little is known about their potential effect in renal disorders. In this study, using the holistic view of systems biology, it was determined that ORs are significantly changed during the progression of kidney fibrosis. For further validation, common differentially expressed ORs resulted from reanalysis of two time-course microarray datasets were selected for experimental evaluation in a validated murine model of unilateral ureteral obstruction (UUO). Transcriptional analysis by real-time quantitative polymerase chain reaction demonstrated considerable changes in the expression pattern of Olfr433, Olfr129, Olfr1393, Olfr161, and Olfr622 during the progression of kidney fibrosis. For localization of these ORs, single-cell RNA-sequencing datasets of normal and UUO mice were reanalyzed. Results showed that Olfr433 is highly expressed in macrophages in day-2 and 7 post-injury in UUO mice and not in normal subgroups. Besides, like previous findings, Olfr1393 was shown to be expressed prominently in the proximal tubular cells of the kidney. In conclusion, our combinatorial temporal approach to the underlying mechanisms of chronic kidney disease highlighted the potential role of ORs in progression of fibrosis. The expression of Olfr433 in the macrophages provides some clue about its relation to molecular mechanisms promoted in the fibrotic kidney. The proposed ORs in this study could be the subject of further functional assessments in the future.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".