MétaCan
Menu
← Back to cohort
Record W2887919367 · doi:10.1113/jp275978

Reply from Luca Ruggiero, Alexandra F. Yacyshyn, Jane Nettleton and Chris J. McNeil

2018· letter· en· W2887919367 on OpenAlexafffund
Luca Ruggiero, Alexandra F. Yacyshyn, Jane Nettleton, Chris J. McNeil

Bibliographic record

VenueThe Journal of Physiology · 2018
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHigh Altitude and Hypoxia
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaInterior Health
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyMedicineHypoxia (environmental)HumanitiesPhysical medicine and rehabilitationArtChemistryOxygen

Abstract

fetched live from OpenAlex

In their letter to the Editor regarding our recent paper, Finn and colleagues propose that the heightened motoneurone responsiveness in chronic hypoxia (CH) compared to acute hypoxia (AH) may relate primarily to greater peripheral fatigue in AH than CH, rather than motoneuronal adaptations to hypoxia. This is an astute observation and, based on the reduction of maximal torque and increase in EMG at the end of the fatigue protocol, an interpretation that could have been addressed in the original article. However, for the reasons described below, we do not believe peripheral fatigue to be a driving influence for our results. We also take this opportunity to discuss the issue of study design (i.e. matched torque vs. matched EMG). Of note, all of the values we report refer to a relative increase or decrease from baseline. After 3 min of exercise, there is a ∼35% reduction in motoneurone excitability (as measured by the cervicomedullary motor evoked potential, CMEP) during a matched EMG contraction in both AH and normoxia (N), whereas the CMEP in CH is reduced only 3% (see Fig. 5B of Ruggiero et al. 2018). Just prior to this time point, the absolute increase in integrated EMG (iEMG) during a matched torque contraction is 13% for AH, 5% for N, and 4% for CH. This AH iEMG is similar to the end-exercise value in CH (+11%), yet the reduction in the CMEP is 36% for AH at 3 min but only 23% for CH at 16 min. Further, despite the absence of a meaningful increase in iEMG from 3 min to 5 min (+3%) in CH, the CMEP at 5 min is reduced 18% and relatively stable thereafter. In N, the CMEP is stable beyond 3 min, despite a continued, gradual increase in iEMG (22% at 16 min). In AH, the CMEP nears its lowest value at 7 min, when the increase in iEMG (28%) is less than half that at task termination (58%). Based on these findings, it is clear that the size of the CMEP is influenced strongly by factors other than the level of peripheral fatigue inferred by EMG. Moreover, the (non-significant) greater reduction in maximal torque in CH compared to N, without a decrease in CMEP size in CH, weakens the link between motoneurone excitability and this alternative index of fatigue. The iEMG data described above argue against a tight relationship between the CMEP and peripheral fatigue; this argument is strengthened if the voluntary EMG data (either integrated or root mean square) are normalized to account for fatigue-related changes to the maximal M-wave (Mmax). When normalized in this fashion, the increase in EMG is equivalent for CH and N and the separation between these conditions and AH is reduced. Although none of the changes are statistically significant (see Fig. 5A of Ruggiero et al. 2018), Mmax size increases with fatigue in N and AH but decreases in CH. To compensate for this reduction in peripheral excitability, greater descending drive would be required in CH compared to N and AH to achieve a targeted level of iEMG. Hence, in a protocol of matched EMG instead of torque, there is the potential to simply flip which condition is likely to experience the greatest fatigue-related increase in motoneurone activation. In the work that compared CMEPs of different sizes (McNeil et al. 2011), the conditions of the fatigue task were identical across the two sessions. With the current study, there were three different conditions (N, AH and CH) and, given the dearth of similar experiments, a limited ability to tailor our design according to previous findings. The nature of the expedition to 5050 m permitted only one attempt to address our research question. After weighing the benefits and limitations of various experimental protocols, we opted for a design that aligned with the acclimatization studies of whole-body exercise (e.g. Goodall et al. 2014); i.e. we chose a submaximal, intermittent protocol with a target (torque) that relates to muscle performance outside of a laboratory setting. As suggested by Finn and colleagues (2018), we agree that it would be prudent for future work to investigate the impact of hypoxia (acute and chronic) on motoneurone excitability during a fatiguing task with only an EMG target. However, based on our novel findings, it is advisable to adjust the EMG target to account for real-time changes to the Mmax. This would be true not only for the environmental conditions considered here, but for any experimental design in which multiple conditions are compared. We thank Finn and colleagues for their interest in our study. It provided us the opportunity to expand on our rationale and interpretations of the data and also make a recommendation for future study design. None declared.

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)0.004
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.018
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.004
Open science0.0020.002
Research integrity0.0180.030
Insufficient payload (model declined to judge)0.0070.008

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 head0.010
GPT teacher head0.232
Teacher spread0.223 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Physiology→Same topicHigh Altitude and Hypoxia→French-language works237,207→