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Effect of simulated microgravity on mesenteric blood flow during orthostatic challenge

2008· article· en· W3177472314 on OpenAlexaffabout
Susan Kaufman, Jody Levasseur

Bibliographic record

VenueThe FASEB Journal · 2008
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineSplanchnicSuperior mesenteric arteryBlood flowOrthostatic intoleranceAnesthesiaOrthostatic vital signsHemodynamicsMesenteric arteriesReflexCardiologyBlood pressureInternal medicineArtery

Abstract

fetched live from OpenAlex

Astronauts, particularly females, suffer from post‐flight orthostatic hypotension. We proposed that microgravity impairs reflex control of the splanchnic circulation during an orthostatic challenge. Female rats were trained to mount a 45% incline (Head up tilt, HUT). They were then implanted with transit time flow probes on the superior mesenteric artery (SMA) and vein (SMV). After 7 days recovery, mesenteric arterial and venous blood flow was measured during HUT. After hindlimb unloading (HU) for 14 days, the responses to HUT were then retested. Baseline SMA and SMV blood flows were 13.7±3.5 and 9.7±0.1mL/min respectively. During HUT these fell (At 5 sec: Δ SMA flow = −7mL/min, Δ SMV flow = −3mL/min; At 10 sec: Δ SMA flow = −4mL/min, Δ SMV flow = −3mL/min). There was thus an immediate mesenteric arterial constriction, and a net loss of ~4mL/min blood from the mesenteric vascular bed. After 14 days HU, there were no such changes in blood flow during HUT i.e. there was no reflex mesenteric arterial constriction and no mobilization of venous blood. We propose microgravity impairs splanchnic control of cardiac preload and afterload during HUT, and contributes to orthostatic hypotension. Canadian 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 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: Bench or experimental · Consensus signal: Bench or experimental
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 head0.012
GPT teacher head0.271
Teacher spread0.259 · 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 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

Citations0
Published2008
Admission routes2
Has abstractyes

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