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Effect of Cold Exposure and Exercise on Carbohydrate and Lipid Metabolism in Persons with Cervical Spinal Cord Injury

2020· article· en· W3017189925 on OpenAlexaff
Kazunari Nishiyama, Yoshi‐ichiro Kamijo, Tomonori Nakata, Jan W. van der Scheer, Fumihiro Tajima

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSupine positionMedicineInternal medicineGlycogenSpinal cord injurySpinal cordEndocrinologyAnesthesiaAnimal scienceBiology

Abstract

fetched live from OpenAlex

Objective Rates of retiring for Oita International Wheelchair Marathon in the last decade were higher with the lower atmospheric temperature below 22°C. The tendency was stronger in persons with cervical spinal cord injury (CSCI) than the other classes ( unpublished data ), which may be associated with deteriorated lipid utilization and a faster depletion of glycogen in a whole body. Our purpose was to examine whether serum profile of lipid in CSCI during cold stress and exercise was different from able‐body persons (AB) or varied dependent on the injury level. Methods [Protocol1] Nine CSCI and 11 AB wore a water‐perfused suit and took a supine position then 33‐°C water was perfused into the suit. After 10‐min measurement of thermoneutral condition, 25‐°C water was perfused for 20min (CS), then perfused 33‐°C water for 60min, while monitoring esophageal (T es ) and mean skin temperatures (T sk ). Blood samples were taken before, just after, 60‐ and 120min after CS. [Protocol2] Six of each CSCI and AB did a 30‐min arm crank exercise at 50% VO 2peak then took a sitting position for 60min as a recovery. Blood samples were taken before, just after and an hour after exercise. [Protocol3] Bloods were sampled from 5 CSCI and 9 thoracic and lumbar SCI (LSCI), who completed a half marathon, before, just after and an hour after the race. Plasma concentrations of adrenaline ([Ad] p ), noradrenaline ([Nor] p ), and glucose ([Glc] p ), and serum concentrations of insulin ([Ins] s ), free fatty acid ([FFA] s ), and total ketone bodies ([tKB] s ) were assessed in all protocols. Results [Protocol1] Tsk decreased by ~2 °C during CS and Tes decreased by ~0.2 °C after CS with no significant differences between groups. VO 2 was similar between groups and remained unchanged throughout the study. Respiratory quotient was significantly decreased in AB after CS but remained unchanged in CSCI. [Ad] p and [Nor] p were lower in CSCI than AB and [Nor] p significantly increased only in AB during recovery. [Glc] p before, immediately and one hour after CS was higher in CSCI but it decreased to the same level as AB 2 hours later. [FFA] s did not differ between groups and decreased after CS in only AB. [tKB] s significantly increased after CS in both groups, but the increase started from 1‐hour recovery in CSCI. [Protocol2] [Ad] p and [Nor] p increased just after exercise in AB but not in CSCI. [Glc] p remained unchanged in both groups but [Ins]s started to decrease just after exercise in CSCI, earlier than AB. [tKB] s increased from the baseline an hour after exercise in CSCI but not in AB, while [FFA] s did not differ between groups. [Protocol3] [Ad] p and [Nor] p was lower in CSCI than LSCI and increased just after the race only in LSCI and returned to the baseline at an hour after the race. [FFA] s increased just after the race in CSCI and remained the higher level at an hour after race, then [tKB] s increased an hour after the race only in CSCI. Both lipid profiles remained unchanged throughout the study in LSCI. Conclusion It is suggested that lipolysis and ketogenesis are likely to enhance in CSCI during cold or exercise. Lipid and glucose metabolisms vary dependent on the injury level with SCI. Support or Funding Information This work was funded by Nachikatsuura Research foundation and Kyoten, Wakayama Med. Univ.

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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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.281
Teacher spread0.264 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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