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Record W4396625743 · doi:10.1111/rda.14570

Effects of different extenders on epigenetic patterns and functional parameters of bull sperm during cryopreservation process

2024· article· en· W4396625743 on OpenAlexaff
Razieh Fouladvandi, Ali Akbar Masoudi, Mehdi Totonchi, Maryam Hezavehei, Mohsen Sharafi

Bibliographic record

VenueReproduction in Domestic Animals · 2024
Typearticle
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsOttawa Fertility Centre
FundersTarbiat Modares University
KeywordsCryopreservationDNA fragmentationSpermAndrologyExtenderBiologySperm motilityEpigeneticsSemenAcrosomeDNA methylationChemistryCell biologyBiochemistryApoptosisMedicineEmbryoGene expression

Abstract

fetched live from OpenAlex

The cryopreservation process induces alterations in cellular parameters and epigenetic patterns in bull sperm, which can be prevented by adding cryoprotectants in the freezing extenders. The purpose of this study was to compare the protective effects of two extenders based on soybean lecithin (SLE) and egg yolk (EYE) on epigenetic patterns and quality parameters of sperm such as motility parameters, mitochondrial membrane integrity, DNA fragmentation, viability, and apoptotic-like changes of bull sperm after cryopreservation. Results demonstrated that cryopreservation significantly (p < .05) reduced the level of DNA global methylation, H3K9 histone acetylation, and H3K4 histone methylation in both frozen groups compared to the fresh sperm. Also, the level of H3K9 acetylation was lower in the frozen SLE group (21.2 ± 1.86) compared to EYE group (15.2 ± 1.86). In addition, the SLE frozen group had a higher percentage of viability, progressive motility, and linearity (LIN) in SLE frozen group compared to EYE frozen group. However, no difference was observed in mitochondrial membrane integrity and DNA fragmentation between SLE and EYE frozen groups. While soybean-lecithin-based extender showed some initial positive impacts of epigenetics and semen parameters, further investigations can provide useful information for better freezing.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.395
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
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 head0.018
GPT teacher head0.274
Teacher spread0.256 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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