Twenty-one days of spirulina supplementation lowers heart rate during submaximal cycling and augments power output during repeated sprints in trained cyclists
Bibliographic record
Abstract
Spirulina supplementation has been reported to improve time to exhaustion and maximal oxygen consumption (V̇O2max). However, there is limited information on its influence over the multiple intensities experienced by cyclists during training and competition. Fifteen trained males (age 40 ± 8 years, V̇O2max 51.14 ± 6.43 mL/min/kg) ingested 6 g/day of spirulina or placebo for 21 days in a double-blinded randomised crossover design, with a 14-day washout period between trials. Participants completed a 1-hour submaximal endurance test at 55% external power output max and a 16.1-km time trial (day 1), followed by a lactate threshold test and repeated sprint performance tests (RSPTs) (day 2). Heart rate (bpm), respiratory exchange ratio, oxygen consumption (mL/min/kg), lactate and glucose (mmol/L), time (seconds), power output (W), and hemoglobin (g/L) were compared across conditions. Following spirulina supplementation, lactate and heart rate were significantly lower (P < 0.05) during submaximal endurance tests (2.05 ± 0.80 mmol/L vs 2.39 ± 0.89 mmol/L and 139 ± 11 bpm vs 144 ± 12 bpm), hemoglobin was significantly higher (152.6 ± 9.0 g/L) than placebo (143.2 ± 8.5 g/L), and peak and average power were significantly higher during RSPTs (968 ± 177 W vs 929 ± 149 W and 770 ± 117 W vs 738 ± 86 W). No differences existed between conditions for all oxygen consumption values, 16.1-km time trial measures, and lactate threshold tests (P > 0.05). Spirulina supplementation reduces homeostatic disturbances during submaximal exercise and augments power output during RSPTs. Novelty: Spirulina supplementation lowers heart rate and blood lactate during ∼1-hour submaximal cycling. Spirulina supplementation elicits significant augmentations in hemoglobin and power outputs during RSPTs.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".