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Record W4385307969 · doi:10.3390/jcm12154928

Paternal Age Matters: Association with Sperm Criteria’s- Spermatozoa DNA Integrity and Methylation Profile

2023· article· en· W4385307969 on OpenAlexaff
Marwa Lahimer, Debbie Montjean, Rosalie Cabry, Severine Capelle, Élodie Lefranc, Véronique Bach, Mounir Ajina, Habib Ben Ali, Hafida Khorsi‐Cauet, Moncef Benkhalifa

Bibliographic record

VenueJournal of Clinical Medicine · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDemographic Trends and Gender Preferences
Canadian institutionsOttawa Fertility Centre
Fundersnot available
KeywordsMedicineDNA methylationSpermAssociation (psychology)MethylationAndrologyGeneticsDNAGeneGene expressionBiology

Abstract

fetched live from OpenAlex

Advanced age has been reported to negatively affect sperm parameters and spermatozoa DNA integrity. A decline in sperm criteria was also associated with altered epigenetic marks such as DNA methylation with a potential downstream impact on in vitro fertilization success and clinical outcomes. The aim of the present retrospective study was to clarify the association between advanced paternal age (APA) and sperm parameters, DNA integrity and DNA methylation profile. A total of 671 patients consulting for infertility underwent sperm analysis, sperm DNA integrity assessment and methylation level measurement. The principal finding was that individuals over 40 years of age exhibit a significant increase in DNA fragmentation levels compared to the younger group (15% versus 9%, respectively, p = 0.04). However, there was no significant difference in DNA decondensation and sperm parameters in association with APA. In addition, a drop in the global methylation level was also found in men over 40 years (6% in the young group versus 2% in the old group, p = 0.03). As a conclusion, men over 40 years are at higher risk of elevated sperm DNA fragmentation and lower methylation level. Based on these observations, it is recommended that the assessment of sperm DNA fragmentation should be taken into consideration particularly after the age of 40. Our findings support the idea that paternal age is a crucial factor that should not be neglected during fertility evaluation and treatment since it is associated with epigenetics changes in sperm. Although the underlying mechanism remains to be clarified, we believe that environmental and professional exposure factors are likely involved in the process.

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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.152
GPT teacher head0.460
Teacher spread0.309 · 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 designObservational
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

Citations33
Published2023
Admission routes1
Has abstractyes

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