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Record W3162650662 · doi:10.1113/ep089648

Jumping at a chance to control cerebral blood flow in astronauts

2021· letter· en· W3162650662 on OpenAlexaff
Damian M. Bailey, Philip N. Ainslie, Lonnie G. Petersen, Peter zu Eulenburg

Bibliographic record

VenueExperimental Physiology · 2021
Typeletter
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaInterior Health
FundersNovo Nordisk Fonden
KeywordsCerebral blood flowHydrostatic pressurePsychologyNeuroscienceMedicineMechanicsPhysicsCardiology

Abstract

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In this issue of Experimental Physiology, Ogoh et al. (2021) explore how gravity (or rather, the lack of!) and exercise impact the delicate balance underlying the regulation of cerebral blood flow (CBF) and outflow. This topic is especially relevant because gravitational acceleration has been a constant force throughout the ∼4 billion years of Earth's history, having helped to shape evolution of the human brain, given the pressure for bipedal locomotion when life transitioned from water to land. Much thanks to its phenomenal processing power, our brain has since developed into a ‘gas-guzzling energy-hog’, demanding a disproportionate chunk of our basal oxygen budget (∼25%) despite weighing <1/50th of our total body mass. Given that the brain is so expensive to run, we are equipped with extensive and sophisticated vasoregulatory mechanisms that preserve cerebral perfusion and substrate delivery, allowing our brains to ‘stand up’ to the seemingly innocuous challenge of ‘standing up’ against the vertical hydrostatic pressure gradient in normogravity (1 GZ) (Bailey, 2019). These familiar hydrostatic pressure gradients are, of course, lost in the weightlessness of space, posing unique challenges for the brain. Indeed, the red, round faces and skinny legs of astronauts floating aboard the International Space Station (ISS) belie an almost 2 litre cephalic shift of blood and cerebrospinal fluid (Moore & Thornton, 1987); a phenomenon coined the ‘Charlie Brown’ or ‘puffy-head bird-legs’ syndrome. These fluid shifts pose a major risk to mission operational success by contributing to headaches, malaise, cognitive impairment and a constellation of adverse changes in visual acuity known collectively as the spaceflight-associated neuro-ocular syndrome (SANS) (Mader et al., 2011). Although its underlying aetiology remains widely contested, especially regarding the role of intracranial hypertension, SANS is among the highest priority human health risks for long-duration spaceflight, including a return trip to the moon and the more ambitious multi-year crewed mission to Mars. Although the long(er)-term implications of SANS for the brain remain completely unknown, they are likely to extend well beyond the eye, sparking intense research efforts to recreate SANS in terrestrial cohorts and develop practical countermeasures to mitigate risks. To that end, Ogoh et al. (2021) sought to determine the extent to which one such potential countermeasure [jump exercise training (JET)] impacts the regulation of CBF in response to the microgravity recreated by 60 day of (−6°) head-down-tilt bed rest (HDTBR). Although HDTBR is not the perfect ‘space simulator’, because it fails to remove the Gx (chest-to-back) loading vector, it is widely considered the most effective terrestrial analogue for recreating the pronounced cephalic fluid shifts and upward (superior–posterior) shift of the brain that potentially predispose to SANS subsequent to head-to-foot gravitational unloading (Figure 1a). Ogoh et al. (2021) used duplex ultrasound mapping of regional changes in the extracranial distribution of conduit arterial and venous blood flow to extend their earlier research demonstrating that over the course of a 60 day campaign, 30 days of HDTBR was sufficient to reduce blood flow to the anterior circulation, whereas posterior perfusion remained preserved (Figure 1b). What caused the selective hypoperfusion is unclear, although potentially related to dynamic cerebral autoregulation-mediated myogenic vasoconstriction to ‘buffer’ initial surges in cerebral perfusion pressure that could destabilize the fragile cellular architecture of the neurovascular unit. Indeed, the observed diversion of flow from the internal to external carotid artery provides indirect support for neuroprotective ‘crosstalk’, although it could equally represent passive redistribution. Another explanation might be an active downregulation of cerebrospinal fluid production through ultrafiltration to counter raised intracranial pressure during HDTBR by means of lowering internal carotid artery pressure levels, because the predominant mass of choroid plexus, which is located in the lateral ventricles, has its arterial input via the anterior choroidal artery from the internal carotid artery (Damkier et al., 2013). Additionally, hypoperfusion might simply reflect reduced cerebral metabolism because, after all, the brain rested mostly idle, with motor/cognitive stimulation supressed. Regardless, these findings certainly justified a countermeasure, given that the microgravity-induced reduction in anterior perfusion could potentially be linked to the ‘space fog’ or cognitive impairment that plagues astronauts and has been linked to poorer landing accuracy in Space Shuttle pilots (Roy-O'Reilly et al., 2021). Indeed, you need look no further than patients who have undergone carotid endarterectomy (an elective surgical procedure that shells out stenotic atherosclerotic plaque at the origin of the carotid artery to prevent a major stroke) to appreciate fully the cognitive gains afforded through revascularization when the anterior circulation is ‘refuelled’. Importantly, in the present publication (Ogoh et al., 2021), JET failed to restore the regional deficits in anterior perfusion, arguing against its suitability as a potential neuroprotective countermeasure. This is frustrating, given the recently documented cardiopulmonary and musculoskeletal benefits conferred by JET and ‘potential’ for sinusoidal hyperaemia incurred during the ‘squat–stand’ nature of exercise previously suggested to compound cerebrovascular endothelial adaptation by optimizing the pressure–strain–shear stress phenotype (Figure 1b) (Calverley et al., 2020). However, before we reject the ‘JET-propelled brain’ completely, there are a few points worth raising. First, we must consider whether the training stimulus was of sufficient magnitude (intensity/frequency/duration) to kick-start cerebrovascular adaptation. Second, the training group was comparatively more hypocapnic (end-tidal was ∼2.5 mmHg lower on day 57 of HDTBR), which probably masked any elevations in CBF by ∼8% and probably contributed to the observed reduction in arterial shear rates owing to cerebral vasoconstriction (assuming 1 mmHg reduction in end-tidal translates into ∼3% reduction in flow). Third, the inherent biological variability associated with the regional mapping of CBF illustrated in figure 2 of their original publication is an equally important take-home message that serves as a sober reminder for future researchers to ensure that their study is adequately powered. The new information presented by Ogoh et al. (2021) makes an important contribution to a complex and clinically relevant topic, while encouraging the need for further research. This quest is especially relevant, given the European Space Agency's recent revamp of the Science in Space Environment research programme, with an eye on deep space exploration to Mars and intensifying efforts to find suitable countermeasures to bolster the brain. D.M.B. is Chair of the Life Sciences Working Group and an ex offico member of the Human Spaceflight and Exploration Science Advisory Committee to the European Space Agency and is a member of the Space Exploration Advisory Committee to the UK Space Agency. Peter zu Eulenburg is a member of the Life Sciences Working Group to the European Space Agency.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.340
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.274
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2021
Admission routes1
Has abstractyes

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