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Record W2743823955 · doi:10.1038/s41598-017-08432-w

Protein expression changes caused by spaceflight as measured for 18 Russian cosmonauts

2017· article· en· W2743823955 on OpenAlexafffund
И. М. Ларина, Andrew J. Percy, Juncong Yang, Christoph H. Borchers, Andrei M. Nosovsky, A. I. Grigoriev, Е. Н. Николаев

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsJewish General HospitalUniversity of Victoria
FundersWarren Y. Soper Charitable TrustFondation De Famille Alvin SegalGenome British ColumbiaMcGill UniversityUniversity of VictoriaJewish General HospitalLeading Edge Endowment FundGenome Canada
KeywordsSpaceflightProteomeProteasesProteomicsBlood proteinsMass spectrometryWeightlessnessLipid metabolismChemistryFunction (biology)BiochemistryBiologyComputational biologyCell biologyChromatographyGeneEnzymePhysics

Abstract

fetched live from OpenAlex

The effects of spaceflight on human physiology is an increasingly studied field, yet the molecular mechanisms driving physiological changes remain unknown. With that in mind, this study was performed to obtain a deeper understanding of changes to the human proteome during space travel, by quantitating a panel of 125 proteins in the blood plasma of 18 Russian cosmonauts who had conducted long-duration missions to the International Space Station. The panel of labeled prototypic tryptic peptides from these proteins covered a concentration range of more than 5 orders of magnitude in human plasma. Quantitation was achieved by a well-established and highly-regarded targeted mass spectrometry approach involving multiple reaction monitoring in conjunction with stable isotope-labeled standards. Linear discriminant function analysis of the quantitative results revealed three distinct groups of proteins: 1) proteins with post-flight protein concentrations remaining stable, 2) proteins whose concentrations recovered slowly, or 3) proteins whose concentrations recovered rapidly to their pre-flight levels. Using a systems biology approach, nearly all of the reacting proteins could be linked to pathways that regulate the activities of proteases, natural immunity, lipid metabolism, coagulation cascades, or extracellular matrix metabolism.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.181
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.319
Teacher spread0.284 · 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.

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

Citations45
Published2017
Admission routes2
Has abstractyes

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