The functional consequence of RhoA knockdown by RNA interference in rat cerebral arteries
Bibliographic record
Abstract
Uridine triphosphate (UTP) constricts cerebral arteries by activating transduction pathways that increase cytosolic [Ca(2+)] and myofilament Ca(2+) sensitivity. The signaling proteins that comprise these pathways remain uncertain with recent studies implicating a role for several G proteins. To start clarifying which G proteins enable UTP-induced vasoconstriction, a small interfering RNA (siRNA) approach was developed to knock down specified targets in rat cerebral arteries. siRNA directed against G(q) and RhoA was introduced into isolated cerebral arteries using reverse permeabilization. Following a defined period of organ culture, arteries were assayed for contractile function, mRNA levels, and protein expression. Targeted siRNA reduced RhoA or G(q) mRNA expression by 60-70%, which correlated with a reduction in RhoA but not G(q) protein expression. UTP-induced constriction was abolished in RhoA-depleted arteries, but this was not due to a reduction in myosin light chain phosphorylation. UTP-induced actin polymerization was attenuated in RhoA-depleted arteries, which would explain the loss of agonist-induced constriction. In summary, this study illustrates that siRNA approaches can be effectively used on intact arteries to induce targeted knockdown given that the protein turnover rate is sufficiently high. It also demonstrates that the principal role of RhoA in agonist-induced constriction is to facilitate the formation of F-actin, the physical structure to which phosphorylated myosin binds to elicit arterial constriction.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".