Mechanism and effects of fructose diphosphate on anti-hypoxia fatigue and learning memory ability
Bibliographic record
Abstract
This study aims to investigate the mechanisms through which fructose diphosphate (FDP) causes anti-hypoxia and anti-fatigue effects and improves learning and memory. Mice were divided into three groups: low-dose FDP (FDP-L), high-dose FDP (FDP-H), and a control group. Acute toxic hypoxia induced by carbon monoxide, sodium nitrite, and potassium cyanide and acute cerebral ischemic hypoxia were used to investigate the anti-hypoxia ability of FDP. The tests of rod-rotating, mouse tail suspension, and swimming endurance were used to explore the anti-fatigue effects of FDP. The Morris water maze experiment was used to determine the impact of FDP on learning and memory ability. Poisoning-induced hypoxic tests showed that mouse survival time was significantly prolonged in the FDP-L and FDP-H groups compared with the control group (p < 0.05). In the exhaustive swimming test, FDP significantly shortened struggling time and prolonged the time of mass-loaded swimming; the rod-rotating test showed that endurance time was significantly prolonged by using FDP (p < 0.05). FDP significantly decreased lactate and urea nitrogen levels and increased hepatic and muscle glycogen and glucose transporter-4 and Na+-K+-ATPase (p < 0.05). To conclude, FDP enhances hypoxia tolerance and fatigue resistance and improves learning and memory ability through regulating glucose and energy metabolism.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".