HCaRG increases renal cell migration by a TGF-α autocrine loop mechanism
Bibliographic record
Abstract
We have shown previously that the hypertension-related, calcium-regulated gene (HCaRG) is involved in the control of renal cell proliferation and differentiation (Devlin AM, Solban N, Tremblay S, Gutkowska J, Schurch W, Orlov SN, Lewanczuk R, Hamet P, and Tremblay J. Am J Physiol Renal Physiol 284: F753-F762, 2003). To determine whether HCaRG plays a role in kidney repair after injury, we extended our studies on the cellular function of HCaRG by comparing cell migration of two kidney cell lines [HEK293 and Madin-Darby canine kidney (MDCK)-C7] stably transfected with the plasmid alone or with a plasmid containing HCaRG cDNA. HCaRG-expressing HEK293 cells, which undergo lower proliferation, migrated faster than control cells and presented greater adhesiveness to the extracellular matrix. Faster migration was also observed for the MDCK-C7 cells, after they were stably transfected with HCaRG cDNA. HCaRG overexpression induced major morphological changes in HEK293 cells, including the formation of lamellipodia. Expression microarrays of HCaRG-expressing HEK293 cells revealed the elevated expression of several genes known to be involved in cell migration and lamellipodia formation, including transforming growth factor-alpha (TGF-alpha), galectins, autotaxins and fibronectin. These cells exhibited augmented synthesis and release of activated TGF-alpha. Conditioned medium from HCaRG-expressing cells stimulated the migration and induced significant morphological changes in control cells, in part, through activation of the TFG-alpha/EGF receptor. Together, these data support a role for HCaRG in kidney repair after injury through its effect on renal cell migration and TGF-alpha secretion.
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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".