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Record W2749933427 · doi:10.1139/apnm-2017-0249

Combined aerobic and resistance exercise training for improving reproductive function in infertile men: a randomized controlled trial

2017· article· en· W2749933427 on OpenAlexvenueno aff
Behzad Hajizadeh Maleki, Bakhtyar Tartibian

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2017
Typearticle
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsnot available
Fundersnot available
KeywordsMalondialdehydeOxidative stressAerobic exerciseSemenMedicineMale infertilitySuperoxide dismutaseInfertilitySpermSemen analysisRandomized controlled trialProinflammatory cytokineInternal medicineInflammationAndrologyPhysiologyPhysical therapyPregnancyBiology

Abstract

fetched live from OpenAlex

This randomized controlled trial was conducted to examine the effects of 24 weeks of combined aerobic and resistance exercise training on seminal markers of inflammation and oxidative stress as well as markers of male reproductive function and reproductive performance in infertile patients. Of a total of 1296 infertile patients (aged 25-40 years) who were screened, 556 were randomly assigned to exercise (n = 278) and nonexercise (n = 278) groups. Semen samples were taken before and at 12 and 24 weeks as well as 7 and 30 days post-intervention. The training program reduced seminal proinflammatory cytokines (interleukin (IL)-1β, IL-6, IL-8, and tumor necrosis factor alpha) and markers of oxidative stress (reactive oxygen species, malondialdehyde, and 8-isoprostane) (P < 0.05). Additional improvements were also achieved in seminal antioxidant defense system (superoxide dismutase, catalase, and total antioxidant capacity) (P < 0.05). Training-induced changes in inflammation and oxidative stress status correlated with favorable improvements in semen parameters, sperm DNA integrity, and pregnancy rate (P < 0.05). In conclusion, these results support the evidence for the favorable effects of combined aerobic and resistance exercise training in male factor infertility.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.017
GPT teacher head0.258
Teacher spread0.241 · 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 designRandomized trial
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

Citations37
Published2017
Admission routes1
Has abstractyes

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