MétaCan
Menu
Back to cohort
Record W4404399795 · doi:10.1038/s41526-024-00443-y

Retinal blood vessel diameter changes with 60-day head-down bedrest are unaffected by antioxidant nutritional cocktail

2024· article· en· W4404399795 on OpenAlexafffund
Tijs Louwies, Patrick De Boever, Robin Hasso, Malcom F. Tremblay, Da Xu, Andrew P. Blaber, Nandu Goswami

Bibliographic record

Venuenpj Microgravity · 2024
Typearticle
Languageen
FieldMedicine
TopicRetinal Imaging and Analysis
Canadian institutionsSimon Fraser University
FundersCanadian Space AgencyGovernment of CanadaEuropean Space Agency
KeywordsAntioxidantRetinalHead (geology)Blood vesselMedicineOphthalmologyAnatomyChemistryInternal medicineBiologyBiochemistry

Abstract

fetched live from OpenAlex

Long-term human spaceflight can lead to cardiovascular deconditioning, but little is known about how weightlessness affects microcirculation. In this study, we examined how the retinal microvessels and cerebrovascular regulation of 19 healthy male participants responded to long-term head-down bedrest (HDBR), an earth-based analog for weightlessness. In addition, we examined whether an anti-inflammatory/antioxidant cocktail could prevent the vascular changes caused by HDBR. In all study participants, we found a decrease in retinal arteriolar diameter by HDBR day 8 and an increase in retinal venular diameter by HDBR day 16. Concurrently, blood pressure at the level of the middle cerebral artery and the cerebrovascular resistance index were higher during HDBR, while cerebral blood flow velocity was lower. None of these changes were reversed in participants receiving the anti-inflammatory/antioxidant cocktail, indicating that this cocktail was insufficient to restore the microvascular and cerebral blood flow changes induced by HDBR.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.264
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations4
Published2024
Admission routes2
Has abstractyes

Explore more

Same venuenpj MicrogravitySame topicRetinal Imaging and AnalysisFrench-language works237,207