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Record W4313456745 · doi:10.29244/avi.10.3.262-269

Potensi Alfa Enolase (ENO1) Membran Plasma Spermatozoa Sapi Bali Sebagai protein Antigenik

2022· article· id· W4313456745 on OpenAlexaff
Teguh Sumarsono, Bambang Purwantara, Iman Supriatna, Mohamad Agus Setiadi, Muhammad Agil

Bibliographic record

VenueActa Veterinaria Indonesiana · 2022
Typearticle
Languageid
FieldAgricultural and Biological Sciences
TopicAquatic life and conservation
Canadian institutionsBombardier Recreational Products (Canada)
Fundersnot available
KeywordsAndrologyMolecular biologyChemistryMedicineBiology

Abstract

fetched live from OpenAlex

Antibodi imunoglobulin G (IgG) merupakan salah satu immunoglobulin yang dikandung oleh antibodi anti-sperma (ASA) yang terdapat pada saluran reproduksi betina. Imunoglobulin G dapt berikatan dengan protein-protein yang berpotensi sebagai protein antigenik seperti alfa enolase (ENO1). Penelitian ini bertujuan untuk mengidentifikasi dinamika dan potensi ENO1 membran plasma spermatozoa sebagai protein antigenik serta kualitas spermatozoa sapi Bali dengan perlakuan 0,5 mg/ml IgG. Sampel penelitian adalah 16 ejakulat yang diperoleh dari 4 ekor pejantan. Motilitas spermatozoa dievaluasi menggunakan CASA, viabilitas melalui metode pewarnaan diferensial, Keutuhan Membran Plasma (MPU) menggunakan metode Hypo-osmotic Swelling Test (HOS-Test), nilai Mix Anti-globulin Reaction (MAR) diperoleh dari MAR-Test, sedangkan kuantitas ENO1 diukur dengan ELISA. Analisis data menggunakan analisis ragam RAK. Hasil penelitian menunjukkan bahwa perlakuan dengan IgG sampai 0,5 mg/ml menurunkan motilitas, kinematika spermatozoa, viabilitas, MPU dan kuantitas ENO1 membran plasma spermatozoa (P<0,01), serta meningkatkan nilai MAR-test (P<0,05). Penelitian menyimpulkan bahwa IgG dapat menurunkan kualitas spermatozoa dan kuantitas ENO1, sekaligus menunjukkan bahwa ENO1 membran plasma spermatozoa sapi Bali berpotensi sebagai protein antigenik.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
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 score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.027
GPT teacher head0.215
Teacher spread0.189 · 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.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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