Scratching the surface of hypoxic cerebral vascular control: a potentially polarizing view of mechanistic research in humans
Bibliographic record
Abstract
Reductions in arterial oxygen content require hypoxic cerebral vasodilatation to increase cerebral blood flow (CBF) and maintain oxygen delivery to the brain. The mechanistic control of hypoxic cerebral vasodilatation has proven difficult to discern in humans and translation from in vitro and in vivo animal studies of hypoxic CBF regulation to human studies has largely faltered. Pharmacological blockade of prototypical vascular signalling pathways, such as adenosine receptor blockade, and inhibition of either prostaglandin or nitric oxide synthesis have not consistently been demonstrated to influence hypoxic cerebral vasodilatation in humans (Hoiland et al. 2016). Authors typically ascribe the lack of observed effect to the multitude of complex and intertwined pathways that regulate hypoxic cerebral vasodilatation and confer redundancy during isolated pharmacological blockade studies. Indeed, when investigating hypoxic cerebral vasodilatation it is important to consider that blood borne and endothelial signalling pathways are relatively superficial (i.e. surface level) compared to the multitude of downstream pathways that trigger smooth muscle hyperpolarization and vasodilatation. Therefore, with regards to characterizing, in vivo, the various mechanisms implicated in the provocation of hypoxic cerebral vasodilatation in humans, it is pertinent to ask: have we been stuck scratching the surface? The study by Rocha et al. (2020) in this issue of The Journal of Physiology investigated the role of ATP-sensitive K+ (KATP) channels in the regulation of hypoxic cerebral vasodilatation in humans. The authors utilized duplex ultrasonography of the internal carotid and vertebral arteries to quantify CBF and radial artery catheterization to quantify arterial oxygen content during eupnoeic breathing and hypoxia. Isocapnia was maintained to selectively interrogate hypoxic mechanisms of cerebral vascular control prior to and following the ingestion of glibenclamide (KATP channel blocker). Therefore, pre- to post-glibenclamide differences in the magnitude of hypoxic cerebral vasodilatation are taken to reflect the contribution of KATP channels to hypoxic cerebral vasodilatation. The study revealed that hypoxic cerebral vasodilatation was reduced by ∼50% following KATP channel blockade. To our knowledge this is the first study to investigate the influence of KATP channel blockade with glibenclamide on hypoxic cerebral vasodilatation in humans. Where other pharmacological blockade studies have not observed an influence on hypoxic cerebral vasodilatation (reviewed in Hoiland et al. 2016), we suspect that the large reduction observed by Rocha et al. is attributable to the convergence of multiple signalling pathways on the KATP channel (Fig. 1). Overall, vasomotor tone is regulated by intracellular calcium concentration and calcium sensitivity. Calcium sensitivity is regulated in part by two separate, yet integrated nucleotide pathways (i.e. cyclic adenosine monophosphate [cAMP] and cyclic guanosine monophosphate [cGMP]), while potassium channels influence calcium concentration through vascular smooth muscle cell hyperpolarization and inhibition of calcium influx through voltage gated Ca2+ channels (Quayle et al. 1997). Figure 1 outlines several pathways that have been implicated in the control of hypoxic cerebral vasodilatation through in vitro and in vivo animal studies. Prostaglandins and adenosine lead to increases in cAMP while nitric oxide leads to increases in cGMP; all three of these pathways will also increase KATP channel conductance (Quayle et al. 1997). Other factors such as intracellular ATP and will also influence KATP channel conductance (Quayle et al. 1997). Therefore, KATP channels are a point of convergence for a multitude of hypoxic vasodilatory pathways. By inhibiting the opening of KATP channels, glibenclamide precludes vascular smooth muscle cell hyperpolarization and closing of voltage gated Ca2+ channels, thereby allowing the vasoconstrictor influence of intracellular Ca2+ to prevail. This manifests in a reduced ability to vasodilate in the context of hypoxia, which is now corroborated by the work of Rocha et al. in humans. The elegant study by Rocha et al. notwithstanding, it remains unclear the extent to which individual contributions from the key prototypical pathways contribute to the net influence observed through KATP channel blockade. For instance, we have demonstrated, through theophylline administration, that adenosine is presumably not required to induce hypoxic cerebral vasodilatation (Hoiland et al. 2017). Similarly, prostaglandin signalling has not been implicated as obligatory for hypoxic cerebral vasodilatation (Hoiland et al. 2016), albeit prostaglandins appear to interact with reactive oxygen species to regulate CBF in hypoxia (Harrell et al. 2019). Unfortunately, no study has utilized volumetric measures of CBF to investigate the influence of nitric oxide on hypoxic cerebral vasodilatation. However, transcranial Doppler studies reviewed in Hoiland et al. (2016) do not indicate that nitric oxide is requisite for hypoxic cerebral vasodilatation. Collectively, these studies reveal that single pathway blockades upstream of KATP channels have been unable to show an impact on the robust compensatory redundancies that maintain cerebral oxygen delivery in the face of hypoxia. To this effect, while ‘scratching the surface’ has not yet provided clear insights into the regulation of cerebral hypoxic vasodilatation, there remains utility in interrogating the specific pathways to precisely discern the independent and interacting roles of these pathways in the control of hypoxic cerebral vasodilatation (Harrell et al. 2019). In conclusion, the work by Rocha et al. provides a large step forward in our understanding of the mechanistic control of hypoxic cerebral vasodilatation in humans. The observation of impaired cerebral vasodilatation as a consequence of glibenclamide ingestion is novel and sets the stage for future research into human CBF control. Indeed, illumination of this relevant signalling pathway should be taken as an impetus to follow up with other models of hypoxia, as a better understanding of signalling pathways will hold relevance for therapeutics and interventions aimed resolving cerebral vascular dysfunction. The authors declare no conflicts, financial or otherwise. All authors have approved the final version of the manuscript and agree to be accountable for all aspects of the work. All persons designated as authors qualify for authorship, and all those who qualify for authorship are listed. No funding was received for this work.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".