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Record W2160655608 · doi:10.1093/humrep/deq110

Levels of semenogelin in human spermatozoa decrease during capacitation: involvement of reactive oxygen species and zinc

2010· article· en· W2160655608 on OpenAlexafffund
Eve de Lamirande, Gilbert Lamothe

Bibliographic record

VenueHuman Reproduction · 2010
Typearticle
Languageen
FieldMedicine
TopicSperm and Testicular Function
Canadian institutionsMcGill UniversityMcGill University Health CentreRoyal Victoria Hospital
FundersCanadian Institutes of Health Research
KeywordsCapacitationReactive oxygen speciesZincAndrologyBiologyChemistryBiochemistrySpermMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Semenogelin (Sg), the main protein of human semen coagulum, prevents sperm capacitation. The objective of this study was to examine the role of Sg and its mechanism of action. METHODS AND RESULTS: Sg blocked sperm capacitation triggered by various stimuli, via inhibition of superoxide anion (O(2)*-; luminescence assay) and nitric oxide (NO*; tested using diaminofluorescein) generation. Triton-soluble and -insoluble sperm fractions contained Sg and Sg peptides (immunoblotting), the level of which decreased with initiation of capacitation. This drop was prevented by superoxide dismutase and NO* synthase inhibitor and was reproduced by addition of O(2)*- and NO*. Zinc (Zn(2+)) blocked and a zinc chelator (TPEN) promoted the decline in Sg levels. There was a decreased labelling of Sg on the head in capacitating spermatozoa with the two fixation techniques tested (immunocytochemistry). Reactive oxygen species (ROS) (O(2)*- and NO*) caused, these changes, and zinc prevented them. Spermatozoa quickly internalized Sg upon incubation and Sg was then rapidly degraded in a zinc-inhibitable manner. CONCLUSIONS: Sg blocked capacitation mainly via inhibition of ROS generation. Spermatozoa appeared permeable to Sg and processed Sg in a zinc-inhibitable fashion. ROS themselves could promote sperm disposal of Sg which maybe one of the mechanisms that allows initiation of capacitation.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.040
GPT teacher head0.278
Teacher spread0.238 · 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 designBench or experimental
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

Citations44
Published2010
Admission routes2
Has abstractyes

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