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Record W2894347903 · doi:10.3389/fphys.2018.01367

High-Intensity Interval Training Is Associated With Alterations in Blood Biomarkers Related to Brain Injury

2018· article· en· W2894347903 on OpenAlexaff
Alex P. Di Battista, Katherine A. Moes, Maria Y. Shiu, Michael G. Hutchison, Nathan W. Churchill, Scott Thomas, Shawn G. Rhind

Bibliographic record

VenueFrontiers in Physiology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicS100 Proteins and Annexins
Canadian institutionsSt. Michael's HospitalUniversity of TorontoDefence Research and Development Canada
Fundersnot available
KeywordsNeurograninMedicineGlial fibrillary acidic proteinInternal medicineBiomarkerHigh-intensity interval trainingConcussionEndocrinologyBiologyPoison control

Abstract

fetched live from OpenAlex

Purpose: Blood biomarkers are a useful tool to study concussion. However, their interpretation is complicated by a number of potential biological confounds, including exercise. This is particularly relevant in military and athletic settings where injury commonly occurs during physical exertion. The impact of high-intensity interval training (HIIT) on putative brain-injury biomarkers remains under-examined. The purpose of this study was to observe the effects of HIIT on a panel of blood biomarkers associated with brain injury. Methods: Eleven healthy, recreationally active males (median age = 29.0, interquartile range = 26.0 – 31.5) performed HIIT on a bicycle ergometer (8-12 x 60-sec intervals at 100% of peak power output, interspersed by 75-sec recovery at 50 W) three times/week for two weeks. Peripheral blood samples were collected before and immediately after HIIT during the first and last training sessions. Plasma concentrations of s100 calcium binding protein beta (S100B), glial fibrillary acidic protein (GFAP), neuron-specific enolase (NSE), brain-derived neurotrophic factor (BDNF), neurogranin (NRGN), peroxiredoxin (PRDX)-6, creatine kinase-BB isoenzyme (CKBB), visinin-like protein (VILIP)-1, von Willebrand factor (vWF), monocyte chemoattractant protein (MCP)-1, matrix metalloproteinase (MMP)-9, and total tau (T-tau) were quantitated by high-sensitivity MULTI-SPOT® immunoassay, on the MesoScale Diagnostics electrochemiluminescence detection platform. Differences in biomarker concentrations in response to HIIT were evaluated by partial least squares discriminant analysis within a repeated-measures bootstrapped framework. Results: Ten of twelve biomarkers were increased pre-to-post HIIT; VILIP-1 remained unchanged, and GFAP was not statistically evaluated due to insufficient detectability. After two weeks of HIIT, T-tau was no longer significantly elevated pre-to-post HIIT, and significant attenuation was noted in the acute responses of NRGN, PRDX-6, MMP-9, and vWF. In addition, compared to session 1, at session 6 pre-exercise concentrations of NSE and VILIP-1 were significantly lower and higher, respectively. Conclusion: Blood biomarkers commonly associated with brain injury are significantly elevated in response to a single bout of HIIT. After a two-week, 6 session training protocol, this response was attenuated for some, but not all markers. While biomarkers continue to provide promise to concussion research, future studies are necessary to disentangle the common biological sequelae to both exercise and brain injury.

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 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 score0.324
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.009
GPT teacher head0.239
Teacher spread0.231 · 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
Published2018
Admission routes1
Has abstractyes

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