Effects of HIIT training and HIIT combined with circuit resistance training on measures of physical fitness, miRNA expression, and metabolic risk factors in overweight/obese middle-aged women
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to examine the effects of 10 weeks of high-intensity interval training (HIIT) and HIIT combined with circuit resistance training (HCRT) on selected measures of physical fitness, the expression of miR-9, -15a, -34a, -145, and - 155 as well as metabolic risk factors including lipid profiles and insulin resistance in middle-aged overweight/obese women. METHODS: Twenty-seven overweight/obese women aged 35-50 yrs. were randomized to HIIT (n = 14) or HCRT (n = 13) groups. The HIIT group performed running exercises (5 reps x 4 min per session) with active recovery between repetitions for 10 weeks with 5 weekly sessions. The HCRT group performed 10 weeks of HIIT and resistance training with 3 weekly HIIT sessions and 2 weekly HCRT sessions. Anthropometric measures (e.g., body mass), selected components of physical fitness (cardiovascular fitness, muscle strength), levels of miRNAs (miR-9, -15a, -34a, -145, and - 155), lipid profiles (total cholesterol; TC, Triglycerides; TG, low-density lipoprotein cholesterol; LDL-C and high-density lipoprotein cholesterol; HDL-C), and insulin resistance; HOMA-IR index, were measured at baseline and week 10. RESULTS: ). A significant group by time interaction, however, was found for the one-repetition maximum (IRM; p < 0.001, ES= 0.751 , moderate). A post-hoc test indicated an increase in the pre-to-post mean 1RM for HCRT (p = 0.001, ES = 1.83, large). There was a significant group by time interaction for miR-155 (p = 0.05, ES = 0.014, trivial). Levels for miR-155 underwent pre-to-post HIIT increases (p = 0.045, ES = 1.232, large). Moreover, there were also significant group by time interactions for TC (p = 0.035, ES = 0.187, trivial), TG (p < 0.001, ES = 0.586, small), LDL-C (p = 0.029, ES = 0.200, small) and HDL-C (p = 0.009, ES = 0.273, small). Post-hoc tests indicated pre-post HCRT decreases for TC (p = 0.001, ES = 1.44, large) and HDL-C (p = 0.001, ES = 1.407, large). HIIT caused pre-to-post decreases in TG (p = 0.001, ES = 0.599, small), and LDL-C (p = 0.001, ES = 0.926, moderate). CONCLUSIONS: Both training regimes did not improve cardiovascular fitness. But, HCRT improved lower/upper limb muscle strength, and HIIT resulted in an increase in miR-155 expression in peripheral blood mononuclear cells. Furthermore, HIIT and HCRT each improved selected metabolic risk factors including lipid profiles and glucose and insulin metabolism in overweight/obese middle-aged women. TRIAL REGISTRATION: OSF, October, 4th 2023. Registration DOI: https://doi.org/10.17605/OSF.IO/UZ92E . osf.io/tc5ky . "Retrospectively registered".
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".