Unique Organization of Actin Cytoskeleton in Magnocellular Vasopressin Neurons in Normal Conditions and in Response to Salt-Loading
Bibliographic record
Abstract
Abstract Magnocellular neurosecretory cells (MNCs) are intrinsically osmosensitive and can be activated by increases in blood osmolality, triggering the release of antidiuretic hormone vasopressin (VP) to promote water retention. Hence, the activity of magnocellular VP neurons is one of the key elements contributing to the regulation of body fluid homeostasis in healthy organisms. Chronic exposure to high dietary salt leads to excessive activation of VP neurons, thereby elevating levels of circulating VP, which can cause increases in blood pressure contributing to salt-dependent hypertension. However, the molecular basis underlying high-salt diet-induced hyperactivation of magnocellular VP neurons remains not fully understood. Previous studies suggest that magnocellular neurosecretory neurons contain a subcortical layer of actin filaments and pharmacological stabilization of this actin network potentiates osmotically-induced activation of magnocellular neurons. Using super-resolution imagingin situ, we investigated the organization of the actin cytoskeleton in rat MNCs under normal physiological conditions and after a chronic increase in blood osmolality following 7 d of salt-loading (SL). We found that, in addition to the subcortical layer of actin filaments, magnocellular VP neurons are endowed with a unique network of cytoplasmic actin filaments throughout their somata. Moreover, we revealed that the density of both subcortical and cytoplasmic actin networks in magnocellular VP neurons is dramatically increased following SL. These results suggest that increased osmo-responsiveness of VP neurons following chronic exposure to high dietary salt may be mediated by the modulation of unique actin networks in magnocellular VP neurons, possibly contributing to elevated blood pressure in this condition.
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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 | 0.000 |
| 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".